Timezone: »
Climate change is one of the greatest problems society has ever faced, with increasingly severe consequences for humanity as natural disasters multiply, sea levels rise, and ecosystems falter. Since climate change is a complex issue, action takes many forms, from designing smart electric grids to tracking greenhouse gas emissions through satellite imagery. While no silver bullet, machine learning can be an invaluable tool in fighting climate change via a wide array of applications and techniques. These applications require algorithmic innovations in machine learning and close collaboration with diverse fields and practitioners. This workshop is intended as a forum for those in the machine learning community who wish to help tackle climate change.
Sat 8:15 a.m. - 8:30 a.m.
|
Welcome and Opening Remarks
(Opening Remarks)
|
🔗 |
Sat 8:30 a.m. - 9:05 a.m.
|
Jeff Dean (Google AI)
(Invited talk)
|
Jeff Dean 🔗 |
Sat 9:05 a.m. - 9:45 a.m.
|
Spotlight talks
|
🔗 |
Sat 9:45 a.m. - 10:30 a.m.
|
Coffee Break + Poster Session
|
🔗 |
Sat 10:30 a.m. - 11:05 a.m.
|
Felix Creutzig (TU Berlin, MCC)
(Invited talk)
|
Felix Creutzig 🔗 |
Sat 11:05 a.m. - 11:15 a.m.
|
Spotlight talks
|
🔗 |
Sat 11:15 a.m. - 12:00 p.m.
|
Climate Change: A Grand Challenge for ML
(Panel Discussion)
|
Yoshua Bengio · Carla Gomes · Andrew Ng · Jeff Dean · Lester Mackey 🔗 |
Sat 12:00 p.m. - 2:00 p.m.
|
Lunch + Poster Session
|
Frederik Gerzer · Bill Yang Cai · Pieter-Jan Hoedt · Kelly Kochanski · Soo Kyung Kim · Yunsung Lee · Sunghyun Park · Sharon Zhou · Martin Gauch · Jonathan Wilson · Joyjit Chatterjee · Shamindra Shrotriya · Dimitri Papadimitriou · Christian Schön · Valentina Zantedeschi · Gabriella Baasch · Willem Waegeman · Gautier Cosne · Dara Farrell · Brendan Lucier · Letif Mones · Caleb Robinson · Tafara Chitsiga · Victor Kristof · Hari Prasanna Das · Yimeng Min · Alexandra Puchko · Alexandra Luccioni · Kyle Story · Jason Hickey · Yue Hu · Björn Lütjens · Zhecheng Wang · Renzhi Jing · Genevieve Flaspohler · Jingfan Wang · Saumya Sinha · Qinghu Tang · Armi Tiihonen · Ruben Glatt · Muge Komurcu · Jan Drgona · Juan Gomez-Romero · Ashish Kapoor · Dylan J Fitzpatrick · Alireza Rezvanifar · Adrian Albert · Olya (Olga) Irzak · Kara Lamb · Ankur Mahesh · Kiwan Maeng · Frederik Kratzert · Sorelle Friedler · Niccolo Dalmasso · Alex Robson · Lindiwe Malobola · Lucas Maystre · Yu-wen Lin · Surya Karthik Mukkavili · Brian Hutchinson · Alexandre Lacoste · Yanbing Wang · Zhengcheng Wang · Yinda Zhang · Victoria Preston · Jacob Pettit · Draguna Vrabie · Miguel Molina-Solana · Tonio Buonassisi · Andrew Annex · Tunai P Marques · Catalin Voss · Johannes Rausch · Max Evans
|
Sat 2:00 p.m. - 2:40 p.m.
|
Carla Gomes (Cornell)
(Invited talk)
|
Carla Gomes 🔗 |
Sat 2:40 p.m. - 3:30 p.m.
|
Spotlight talks
|
🔗 |
Sat 3:30 p.m. - 4:15 p.m.
|
Coffee Break + Poster Session
|
🔗 |
Sat 4:15 p.m. - 4:40 p.m.
|
Lester Mackey (Microsoft Research and Stanford)
(Invited talk)
|
Lester Mackey 🔗 |
Sat 4:40 p.m. - 5:00 p.m.
|
Spotlight talks
|
🔗 |
Sat 5:00 p.m. - 6:00 p.m.
|
Practical Challenges in Applying ML to Climate Change
(Panel Discussion)
|
Jennifer Chayes · John Platt · Felix Creutzig · Marta Gonzalez · Craig Miller 🔗 |
Author Information
David Rolnick (UPenn)
Priya Donti (Carnegie Mellon University)
Lynn Kaack (ETH Zurich)
Alexandre Lacoste (Element AI)
Tegan Maharaj (MILA)
Andrew Ng (Stanford University)
Andrew Ng, Chief Scientist at Baidu, Chairman & Co-Founder of Coursera, Adjunct Professor, Stanford Dr. Andrew Ng joined Baidu in May 2014 as chief scientist. He is responsible for driving the company's global AI strategy and infrastructure. He leads Baidu Research in Beijing and Silicon Valley as well as technical teams in the areas of speech, big data and image search. In addition to his role at Baidu, Dr. Ng is an adjunct professor in the computer science department at Stanford University. In 2011 he led the development of Stanford's Massive Open Online Course (MOOC) platform and taught an online machine learning class that was offered to over 100,000 students. This led to the co-founding of Coursera, where he continues to serve as chairman. Previously, Dr. Ng was the founding lead of the Google Brain deep learning project. Dr. Ng has authored or co-authored over 100 research papers in machine learning, robotics and related fields. In 2013 he was named to the Time 100 list of the most influential persons in the world. He holds degrees from Carnegie Mellon University, MIT and the University of California, Berkeley.
John Platt (Google)
Jennifer Chayes (Microsoft Research)
Jennifer Chayes is Technical Fellow and Managing Director of Microsoft Research New England, New York City, and Montreal. She was for many years Professor of Mathematics at UCLA. She is author of over 140 academic papers and inventor of over 30 patents. Her research areas include phase transitions in computer science, structural and dynamical properties of networks, graph theory, graph algorithms, and computational biology. She is one of the inventors of the field of graphons, which are now widely used in the machine learning of massive networks. Chayes’ recent work focuses on machine learning, broadly defined. Chayes holds a BA in physics and biology from Wesleyan, where she graduated first in her class, and a PhD in physics from Princeton. She was a postdoctoral fellow at Harvard and Cornell. She is the recipient of the NSF Postdoc Fellowship, the Sloan Fellowship, the UCLA Distinguished Teaching Award, and the Anita Borg Institute Women of Leadership Vision Award. She has twice been a member of the Institute for Advanced Study in Princeton. Chayes is Fellow of the American Association for the Advancement of Science, the Fields Institute, the Association for Computing Machinery, and the American Mathematical Society, and the American Academy of Arts and Sciences. She is the winner of the 2015 John von Neumann Lecture Award, the highest honor of the Society of Industrial and Applied Mathematics. In 2016, she received an Honorary Doctorate from Leiden University. Chayes serves on numerous scientific boards and committees. She is a past VP of the American Mathematical Society, past Chair of Mathematics for the Association for the Advancement of Science, and past Chair of the Turing Award Selection Committee. She is also committed to diversity in the science and technology, and serves on many boards to increase representation of women and minorities in STEM.
Yoshua Bengio (Mila)
Yoshua Bengio is Full Professor in the computer science and operations research department at U. Montreal, scientific director and founder of Mila and of IVADO, Turing Award 2018 recipient, Canada Research Chair in Statistical Learning Algorithms, as well as a Canada AI CIFAR Chair. He pioneered deep learning and has been getting the most citations per day in 2018 among all computer scientists, worldwide. He is an officer of the Order of Canada, member of the Royal Society of Canada, was awarded the Killam Prize, the Marie-Victorin Prize and the Radio-Canada Scientist of the year in 2017, and he is a member of the NeurIPS advisory board and co-founder of the ICLR conference, as well as program director of the CIFAR program on Learning in Machines and Brains. His goal is to contribute to uncover the principles giving rise to intelligence through learning, as well as favour the development of AI for the benefit of all.
More from the Same Authors
-
2021 : RadGraph: Extracting Clinical Entities and Relations from Radiology Reports »
Saahil Jain · Ashwin Agrawal · Adriel Saporta · Steven Truong · Du Nguyen Duong · Tan Bui · Pierre Chambon · Yuhao Zhang · Matthew Lungren · Andrew Ng · Curtis Langlotz · Pranav Rajpurkar -
2021 : Q-Pain: A Question Answering Dataset to Measure Social Bias in Pain Management »
Cécile Logé · Emily Ross · David Dadey · Saahil Jain · Adriel Saporta · Andrew Ng · Pranav Rajpurkar -
2021 Spotlight: Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization »
Kartik Ahuja · Ethan Caballero · Dinghuai Zhang · Jean-Christophe Gagnon-Audet · Yoshua Bengio · Ioannis Mitliagkas · Irina Rish -
2021 : Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning »
Nan Rosemary Ke · Aniket Didolkar · Sarthak Mittal · Anirudh Goyal · Guillaume Lajoie · Stefan Bauer · Danilo Jimenez Rezende · Yoshua Bengio · Chris Pal · Michael Mozer -
2021 : Long-Term Credit Assignment via Model-based Temporal Shortcuts »
Michel Ma · Pierluca D'Oro · Yoshua Bengio · Pierre-Luc Bacon -
2021 : A Consciousness-Inspired Planning Agent for Model-Based Reinforcement Learning »
Mingde Zhao · Zhen Liu · Sitao Luan · Shuyuan Zhang · Doina Precup · Yoshua Bengio -
2021 : Effect of diversity in Meta-Learning »
Ramnath Kumar · Tristan Deleu · Yoshua Bengio -
2021 : Learning Neural Causal Models with Active Interventions »
Nino Scherrer · Olexa Bilaniuk · Yashas Annadani · Anirudh Goyal · Patrick Schwab · Bernhard Schölkopf · Michael Mozer · Yoshua Bengio · Stefan Bauer · Nan Rosemary Ke -
2021 : Multi-Domain Balanced Sampling Improves Out-of-Distribution Generalization of Chest X-ray Pathology Prediction Models »
Enoch Tetteh · David Krueger · Joseph Paul Cohen · Yoshua Bengio -
2022 Poster: Discrete Compositional Representations as an Abstraction for Goal Conditioned Reinforcement Learning »
Riashat Islam · Hongyu Zang · Anirudh Goyal · Alex Lamb · Kenji Kawaguchi · Xin Li · Romain Laroche · Yoshua Bengio · Remi Tachet des Combes -
2022 : Posterior samples of source galaxies in strong gravitational lenses with score-based priors »
Alexandre Adam · Adam Coogan · Nikolay Malkin · Ronan Legin · Laurence Perreault-Levasseur · Yashar Hezaveh · Yoshua Bengio -
2022 : Designing Biological Sequences via Meta-Reinforcement Learning and Bayesian Optimization »
Leo Feng · Padideh Nouri · Aneri Muni · Yoshua Bengio · Pierre-Luc Bacon -
2022 : Bayesian Dynamic Causal Discovery »
Alexander Tong · Lazar Atanackovic · Jason Hartford · Yoshua Bengio -
2022 : Object-centric causal representation learning »
Amin Mansouri · Jason Hartford · Kartik Ahuja · Yoshua Bengio -
2022 : Equivariance with Learned Canonical Mappings »
Oumar Kaba · Arnab Mondal · Yan Zhang · Yoshua Bengio · Siamak Ravanbakhsh -
2022 : Interventional Causal Representation Learning »
Kartik Ahuja · Yixin Wang · Divyat Mahajan · Yoshua Bengio -
2022 : Multi-Objective GFlowNets »
Moksh Jain · Sharath Chandra Raparthy · Alex Hernandez-Garcia · Jarrid Rector-Brooks · Yoshua Bengio · Santiago Miret · Emmanuel Bengio -
2022 : PhAST: Physics-Aware, Scalable, and Task-specific GNNs for accelerated catalyst design »
ALEXANDRE DUVAL · Victor Schmidt · Alex Hernandez-Garcia · Santiago Miret · Yoshua Bengio · David Rolnick -
2022 : Efficient Queries Transformer Neural Processes »
Leo Feng · Hossein Hajimirsadeghi · Yoshua Bengio · Mohamed Osama Ahmed -
2022 : Rethinking Learning Dynamics in RL using Adversarial Networks »
Ramnath Kumar · Tristan Deleu · Yoshua Bengio -
2022 : Consistent Training via Energy-Based GFlowNets for Modeling Discrete Joint Distributions »
Chanakya Ekbote · Moksh Jain · Payel Das · Yoshua Bengio -
2022 : A General-Purpose Neural Architecture for Geospatial Systems »
Martin Weiss · Nasim Rahaman · Frederik Träuble · Francesco Locatello · Alexandre Lacoste · Yoshua Bengio · Erran Li Li · Chris Pal · Bernhard Schölkopf -
2022 : Interventional Causal Representation Learning »
Kartik Ahuja · Yixin Wang · Divyat Mahajan · Yoshua Bengio -
2022 : Interventional Causal Representation Learning »
Kartik Ahuja · Yixin Wang · Divyat Mahajan · Yoshua Bengio -
2022 Workshop: Tackling Climate Change with Machine Learning »
Peetak Mitra · Maria João Sousa · Mark Roth · Jan Drgona · Emma Strubell · Yoshua Bengio -
2022 Spotlight: Lightning Talks 2A-4 »
Sarthak Mittal · Richard Grumitt · Zuoyu Yan · Lihao Wang · Dongsheng Wang · Alexander Korotin · Jiangxin Sun · Ankit Gupta · Vage Egiazarian · Tengfei Ma · Yi Zhou · Yi.shi Xu · Albert Gu · Biwei Dai · Chunyu Wang · Yoshua Bengio · Uros Seljak · Miaoge Li · Guillaume Lajoie · Yiqun Wang · Liangcai Gao · Lingxiao Li · Jonathan Berant · Huang Hu · Xiaoqing Zheng · Zhibin Duan · Hanjiang Lai · Evgeny Burnaev · Zhi Tang · Zhi Jin · Xuanjing Huang · Chaojie Wang · Yusu Wang · Jian-Fang Hu · Bo Chen · Chao Chen · Hao Zhou · Mingyuan Zhou -
2022 Spotlight: Is a Modular Architecture Enough? »
Sarthak Mittal · Yoshua Bengio · Guillaume Lajoie -
2022 : Equivariance with Learned Canonical Mappings »
Oumar Kaba · Arnab Mondal · Yan Zhang · Yoshua Bengio · Siamak Ravanbakhsh -
2022 : Invited Keynote 1 »
Yoshua Bengio -
2022 : FL Games: A Federated Learning Framework for Distribution Shifts »
Sharut Gupta · Kartik Ahuja · Mohammad Havaei · Niladri Chatterjee · Yoshua Bengio -
2022 : Panel Discussion »
Cheng Zhang · Mihaela van der Schaar · Ilya Shpitser · Aapo Hyvarinen · Yoshua Bengio · Bernhard Schölkopf -
2022 Workshop: AI for Science: Progress and Promises »
Yi Ding · Yuanqi Du · Tianfan Fu · Hanchen Wang · Anima Anandkumar · Yoshua Bengio · Anthony Gitter · Carla Gomes · Aviv Regev · Max Welling · Marinka Zitnik -
2022 Poster: Controlled Sparsity via Constrained Optimization or: How I Learned to Stop Tuning Penalties and Love Constraints »
Jose Gallego-Posada · Juan Ramirez · Akram Erraqabi · Yoshua Bengio · Simon Lacoste-Julien -
2022 Poster: MAgNet: Mesh Agnostic Neural PDE Solver »
Oussama Boussif · Yoshua Bengio · Loubna Benabbou · Dan Assouline -
2022 Poster: Neural Attentive Circuits »
Martin Weiss · Nasim Rahaman · Francesco Locatello · Chris Pal · Yoshua Bengio · Bernhard Schölkopf · Erran Li Li · Nicolas Ballas -
2022 Poster: Weakly Supervised Representation Learning with Sparse Perturbations »
Kartik Ahuja · Jason Hartford · Yoshua Bengio -
2022 Poster: Trajectory balance: Improved credit assignment in GFlowNets »
Nikolay Malkin · Moksh Jain · Emmanuel Bengio · Chen Sun · Yoshua Bengio -
2022 Poster: Temporal Latent Bottleneck: Synthesis of Fast and Slow Processing Mechanisms in Sequence Learning »
Aniket Didolkar · Kshitij Gupta · Anirudh Goyal · Nitesh Bharadwaj Gundavarapu · Alex Lamb · Nan Rosemary Ke · Yoshua Bengio -
2022 Poster: Is a Modular Architecture Enough? »
Sarthak Mittal · Yoshua Bengio · Guillaume Lajoie -
2022 : Keynote talk: A Deep Learning Journey »
Yoshua Bengio -
2021 : Live Q&A Session 2 with Susan Athey, Yoshua Bengio, Sujeeth Bharadwaj, Jane Wang, Joshua Vogelstein, Weiwei Yang »
Susan Athey · Yoshua Bengio · Sujeeth Bharadwaj · Jane Wang · Weiwei Yang · Joshua T Vogelstein -
2021 : Discussion Panel 1: Decision Making »
Lieve M.L Helsen · Lynn Kaack · João M. Costa Sousa · Eliane Ubalijoro -
2021 : Live Q&A Session 1 with Yoshua Bengio, Leyla Isik, Konrad Kording, Bernhard Scholkopf, Amit Sharma, Joshua Vogelstein, Weiwei Yang »
Yoshua Bengio · Leyla Isik · Konrad Kording · Bernhard Schölkopf · Joshua T Vogelstein · Weiwei Yang -
2021 Workshop: Tackling Climate Change with Machine Learning »
Maria João Sousa · Hari Prasanna Das · Sally Simone Fobi · Jan Drgona · Tegan Maharaj · Yoshua Bengio -
2021 : General Discussion 1 - What is out of distribution (OOD) generalization and why is it important? with Yoshua Bengio, Leyla Isik, Max Welling »
Yoshua Bengio · Leyla Isik · Max Welling · Joshua T Vogelstein · Weiwei Yang -
2021 : AI X Discovery »
Yoshua Bengio -
2021 : Panel Discussion 2 »
Susan L Epstein · Yoshua Bengio · Lucina Uddin · Rohan Paul · Steve Fleming -
2021 : Desiderata and ML Research Programme for Higher-Level Cognition »
Yoshua Bengio -
2021 Workshop: Causal Inference & Machine Learning: Why now? »
Elias Bareinboim · Bernhard Schölkopf · Terrence Sejnowski · Yoshua Bengio · Judea Pearl -
2021 Poster: Dynamic Inference with Neural Interpreters »
Nasim Rahaman · Muhammad Waleed Gondal · Shruti Joshi · Peter Gehler · Yoshua Bengio · Francesco Locatello · Bernhard Schölkopf -
2021 Poster: Gradient Starvation: A Learning Proclivity in Neural Networks »
Mohammad Pezeshki · Oumar Kaba · Yoshua Bengio · Aaron Courville · Doina Precup · Guillaume Lajoie -
2021 Poster: A Consciousness-Inspired Planning Agent for Model-Based Reinforcement Learning »
Mingde Zhao · Zhen Liu · Sitao Luan · Shuyuan Zhang · Doina Precup · Yoshua Bengio -
2021 Poster: Neural Production Systems »
Anirudh Goyal · Aniket Didolkar · Nan Rosemary Ke · Charles Blundell · Philippe Beaudoin · Nicolas Heess · Michael Mozer · Yoshua Bengio -
2021 Poster: Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation »
Emmanuel Bengio · Moksh Jain · Maksym Korablyov · Doina Precup · Yoshua Bengio -
2021 Poster: The Causal-Neural Connection: Expressiveness, Learnability, and Inference »
Kevin Xia · Kai-Zhan Lee · Yoshua Bengio · Elias Bareinboim -
2021 Poster: Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization »
Kartik Ahuja · Ethan Caballero · Dinghuai Zhang · Jean-Christophe Gagnon-Audet · Yoshua Bengio · Ioannis Mitliagkas · Irina Rish -
2021 Poster: Discrete-Valued Neural Communication »
Dianbo Liu · Alex Lamb · Kenji Kawaguchi · Anirudh Goyal · Chen Sun · Michael Mozer · Yoshua Bengio -
2021 : RadGraph: Extracting Clinical Entities and Relations from Radiology Reports »
Saahil Jain · Ashwin Agrawal · Adriel Saporta · Steven Truong · Du Nguyen Duong · Tan Bui · Pierre Chambon · Yuhao Zhang · Matthew Lungren · Andrew Ng · Curtis Langlotz · Pranav Rajpurkar -
2021 : Q-Pain: A Question Answering Dataset to Measure Social Bias in Pain Management »
Cécile Logé · Emily Ross · David Dadey · Saahil Jain · Adriel Saporta · Andrew Ng · Pranav Rajpurkar -
2020 : Panel discussion 2 »
Danielle S Bassett · Yoshua Bengio · Cristina Savin · David Duvenaud · Anna Choromanska · Yanping Huang -
2020 : Invited Talk Yoshua Bengio »
Yoshua Bengio -
2020 : Invited Talk #7 »
Yoshua Bengio -
2020 : Andrew Ng: Practical limitations of today's deep learning in healthcare »
Andrew Ng -
2020 : Panel #1 »
Yoshua Bengio · Daniel Kahneman · Henry Kautz · Luis Lamb · Gary Marcus · Francesca Rossi -
2020 : Yoshua Bengio - Incentives for Researchers »
Yoshua Bengio -
2020 Workshop: Tackling Climate Change with ML »
David Dao · Evan Sherwin · Priya Donti · Lauren Kuntz · Lynn Kaack · Yumna Yusuf · David Rolnick · Catherine Nakalembe · Claire Monteleoni · Yoshua Bengio -
2020 Poster: Untangling tradeoffs between recurrence and self-attention in artificial neural networks »
Giancarlo Kerg · Bhargav Kanuparthi · Anirudh Goyal · Kyle Goyette · Yoshua Bengio · Guillaume Lajoie -
2020 Poster: Your GAN is Secretly an Energy-based Model and You Should Use Discriminator Driven Latent Sampling »
Tong Che · Ruixiang ZHANG · Jascha Sohl-Dickstein · Hugo Larochelle · Liam Paull · Yuan Cao · Yoshua Bengio -
2020 Poster: Online Fast Adaptation and Knowledge Accumulation (OSAKA): a New Approach to Continual Learning »
Massimo Caccia · Pau Rodriguez · Oleksiy Ostapenko · Fabrice Normandin · Min Lin · Lucas Page-Caccia · Issam Hadj Laradji · Irina Rish · Alexandre Lacoste · David Vázquez · Laurent Charlin -
2020 Poster: Hybrid Models for Learning to Branch »
Prateek Gupta · Maxime Gasse · Elias Khalil · Pawan K Mudigonda · Andrea Lodi · Yoshua Bengio -
2020 Poster: Differentiable Causal Discovery from Interventional Data »
Philippe Brouillard · Sébastien Lachapelle · Alexandre Lacoste · Simon Lacoste-Julien · Alexandre Drouin -
2020 Poster: Synbols: Probing Learning Algorithms with Synthetic Datasets »
Alexandre Lacoste · Pau Rodríguez López · Frederic Branchaud-Charron · Parmida Atighehchian · Massimo Caccia · Issam Hadj Laradji · Alexandre Drouin · Matthew Craddock · Laurent Charlin · David Vázquez -
2020 Spotlight: Differentiable Causal Discovery from Interventional Data »
Philippe Brouillard · Sébastien Lachapelle · Alexandre Lacoste · Simon Lacoste-Julien · Alexandre Drouin -
2019 : Panel Session: A new hope for neuroscience »
Yoshua Bengio · Blake Richards · Timothy Lillicrap · Ila Fiete · David Sussillo · Doina Precup · Konrad Kording · Surya Ganguli -
2019 : Practical Challenges in Applying ML to Climate Change »
Jennifer Chayes · John Platt · Felix Creutzig · Marta Gonzalez · Craig Miller -
2019 : Yoshua Bengio - Towards compositional understanding of the world by agent-based deep learning »
Yoshua Bengio -
2019 : Lunch Break and Posters »
Xingyou Song · Elad Hoffer · Wei-Cheng Chang · Jeremy Cohen · Jyoti Islam · Yaniv Blumenfeld · Andreas Madsen · Jonathan Frankle · Sebastian Goldt · Satrajit Chatterjee · Abhishek Panigrahi · Alex Renda · Brian Bartoldson · Israel Birhane · Aristide Baratin · Niladri Chatterji · Roman Novak · Jessica Forde · YiDing Jiang · Yilun Du · Linara Adilova · Michael Kamp · Berry Weinstein · Itay Hubara · Tal Ben-Nun · Torsten Hoefler · Daniel Soudry · Hsiang-Fu Yu · Kai Zhong · Yiming Yang · Inderjit Dhillon · Jaime Carbonell · Yanqing Zhang · Dar Gilboa · Johannes Brandstetter · Alexander R Johansen · Gintare Karolina Dziugaite · Raghav Somani · Ari Morcos · Freddie Kalaitzis · Hanie Sedghi · Lechao Xiao · John Zech · Muqiao Yang · Simran Kaur · Qianli Ma · Yao-Hung Hubert Tsai · Ruslan Salakhutdinov · Sho Yaida · Zachary Lipton · Daniel Roy · Michael Carbin · Florent Krzakala · Lenka Zdeborová · Guy Gur-Ari · Ethan Dyer · Dilip Krishnan · Hossein Mobahi · Samy Bengio · Behnam Neyshabur · Praneeth Netrapalli · Kris Sankaran · Julien Cornebise · Yoshua Bengio · Vincent Michalski · Samira Ebrahimi Kahou · Md Rifat Arefin · Jiri Hron · Jaehoon Lee · Jascha Sohl-Dickstein · Samuel Schoenholz · David Schwab · Dongyu Li · Sang Keun Choe · Henning Petzka · Ashish Verma · Zhichao Lin · Cristian Sminchisescu -
2019 : Climate Change: A Grand Challenge for ML »
Yoshua Bengio · Carla Gomes · Andrew Ng · Jeff Dean · Lester Mackey -
2019 Workshop: Joint Workshop on AI for Social Good »
Fei Fang · Joseph Aylett-Bullock · Marc-Antoine Dilhac · Brian Green · natalie saltiel · Dhaval Adjodah · Jack Clark · Sean McGregor · Margaux Luck · Jonathan Penn · Tristan Sylvain · Geneviève Boucher · Sydney Swaine-Simon · Girmaw Abebe Tadesse · Myriam Côté · Anna Bethke · Yoshua Bengio -
2019 : Opening remarks »
Yoshua Bengio -
2019 : Approaches to Understanding AI »
Yoshua Bengio · Roel Dobbe · Madeleine Elish · Joshua Kroll · Jacob Metcalf · Jack Poulson -
2019 : Invited Talk »
Yoshua Bengio -
2019 Workshop: Retrospectives: A Venue for Self-Reflection in ML Research »
Ryan Lowe · Yoshua Bengio · Joelle Pineau · Michela Paganini · Jessica Forde · Shagun Sodhani · Abhishek Gupta · Joel Lehman · Peter Henderson · Kanika Madan · Koustuv Sinha · Xavier Bouthillier -
2019 Poster: How to Initialize your Network? Robust Initialization for WeightNorm & ResNets »
Devansh Arpit · Víctor Campos · Yoshua Bengio -
2019 Poster: Wasserstein Dependency Measure for Representation Learning »
Sherjil Ozair · Corey Lynch · Yoshua Bengio · Aaron van den Oord · Sergey Levine · Pierre Sermanet -
2019 Poster: Unsupervised State Representation Learning in Atari »
Ankesh Anand · Evan Racah · Sherjil Ozair · Yoshua Bengio · Marc-Alexandre Côté · R Devon Hjelm -
2019 Poster: Variational Temporal Abstraction »
Taesup Kim · Sungjin Ahn · Yoshua Bengio -
2019 Poster: Gradient based sample selection for online continual learning »
Rahaf Aljundi · Min Lin · Baptiste Goujaud · Yoshua Bengio -
2019 Poster: MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis »
Kundan Kumar · Rithesh Kumar · Thibault de Boissiere · Lucas Gestin · Wei Zhen Teoh · Jose Sotelo · Alexandre de Brébisson · Yoshua Bengio · Aaron Courville -
2019 Invited Talk: From System 1 Deep Learning to System 2 Deep Learning »
Yoshua Bengio -
2019 Poster: Experience Replay for Continual Learning »
David Rolnick · Arun Ahuja · Jonathan Richard Schwarz · Timothy Lillicrap · Gregory Wayne -
2019 Poster: On Adversarial Mixup Resynthesis »
Christopher Beckham · Sina Honari · Alex Lamb · Vikas Verma · Farnoosh Ghadiri · R Devon Hjelm · Yoshua Bengio · Chris Pal -
2019 Poster: Updates of Equilibrium Prop Match Gradients of Backprop Through Time in an RNN with Static Input »
Maxence Ernoult · Julie Grollier · Damien Querlioz · Yoshua Bengio · Benjamin Scellier -
2019 Poster: Deep ReLU Networks Have Surprisingly Few Activation Patterns »
Boris Hanin · David Rolnick -
2019 Poster: Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics »
Giancarlo Kerg · Kyle Goyette · Maximilian Puelma Touzel · Gauthier Gidel · Eugene Vorontsov · Yoshua Bengio · Guillaume Lajoie -
2019 Oral: Updates of Equilibrium Prop Match Gradients of Backprop Through Time in an RNN with Static Input »
Maxence Ernoult · Julie Grollier · Damien Querlioz · Yoshua Bengio · Benjamin Scellier -
2018 : Inverse Optimal Power Flow: Assessing the Vulnerability of Power Grid Data »
Priya Donti -
2018 : Opening remarks »
Yoshua Bengio -
2018 Workshop: AI for social good »
Margaux Luck · Tristan Sylvain · Joseph Paul Cohen · Arsene Fansi Tchango · Valentine Goddard · Aurelie Helouis · Yoshua Bengio · Sam Greydanus · Cody Wild · Taras Kucherenko · Arya Farahi · Jonathan Penn · Sean McGregor · Mark Crowley · Abhishek Gupta · Kenny Chen · Myriam Côté · Rediet Abebe -
2018 Poster: Image-to-image translation for cross-domain disentanglement »
Abel Gonzalez-Garcia · Joost van de Weijer · Yoshua Bengio -
2018 Poster: MetaGAN: An Adversarial Approach to Few-Shot Learning »
Ruixiang ZHANG · Tong Che · Zoubin Ghahramani · Yoshua Bengio · Yangqiu Song -
2018 Poster: Improving Explorability in Variational Inference with Annealed Variational Objectives »
Chin-Wei Huang · Shawn Tan · Alexandre Lacoste · Aaron Courville -
2018 Poster: Bayesian Model-Agnostic Meta-Learning »
Jaesik Yoon · Taesup Kim · Ousmane Dia · Sungwoong Kim · Yoshua Bengio · Sungjin Ahn -
2018 Poster: Sparse Attentive Backtracking: Temporal Credit Assignment Through Reminding »
Nan Rosemary Ke · Anirudh Goyal · Olexa Bilaniuk · Jonathan Binas · Michael Mozer · Chris Pal · Yoshua Bengio -
2018 Spotlight: Sparse Attentive Backtracking: Temporal Credit Assignment Through Reminding »
Nan Rosemary Ke · Anirudh Goyal · Olexa Bilaniuk · Jonathan Binas · Michael Mozer · Chris Pal · Yoshua Bengio -
2018 Spotlight: Bayesian Model-Agnostic Meta-Learning »
Jaesik Yoon · Taesup Kim · Ousmane Dia · Sungwoong Kim · Yoshua Bengio · Sungjin Ahn -
2018 Poster: TADAM: Task dependent adaptive metric for improved few-shot learning »
Boris Oreshkin · Pau Rodríguez López · Alexandre Lacoste -
2018 Poster: Dendritic cortical microcircuits approximate the backpropagation algorithm »
João Sacramento · Rui Ponte Costa · Yoshua Bengio · Walter Senn -
2018 Oral: Dendritic cortical microcircuits approximate the backpropagation algorithm »
João Sacramento · Rui Ponte Costa · Yoshua Bengio · Walter Senn -
2017 : Yoshua Bengio »
Yoshua Bengio -
2017 : From deep learning of disentangled representations to higher-level cognition »
Yoshua Bengio -
2017 : More Steps towards Biologically Plausible Backprop »
Yoshua Bengio -
2017 : A3T: Adversarially Augmented Adversarial Training »
Aristide Baratin · Simon Lacoste-Julien · Yoshua Bengio · Akram Erraqabi -
2017 : Competition III: The Conversational Intelligence Challenge »
Mikhail Burtsev · Ryan Lowe · Iulian Vlad Serban · Yoshua Bengio · Alexander Rudnicky · Alan W Black · Shrimai Prabhumoye · Artem Rodichev · Nikita Smetanin · Denis Fedorenko · CheongAn Lee · EUNMI HONG · Hwaran Lee · Geonmin Kim · Nicolas Gontier · Atsushi Saito · Andrey Gershfeld · Artem Burachenok -
2017 : Jennifer Chayes, Microsoft Research New England »
Jennifer Chayes -
2017 Poster: Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net »
Anirudh Goyal · Nan Rosemary Ke · Surya Ganguli · Yoshua Bengio -
2017 Poster: Thy Friend is My Friend: Iterative Collaborative Filtering for Sparse Matrix Estimation »
Christian Borgs · Jennifer Chayes · Christina Lee · Devavrat Shah -
2017 Demonstration: A Deep Reinforcement Learning Chatbot »
Iulian Vlad Serban · Chinnadhurai Sankar · Mathieu Germain · Saizheng Zhang · Zhouhan Lin · Sandeep Subramanian · Taesup Kim · Michael Pieper · Sarath Chandar · Nan Rosemary Ke · Sai Rajeswar Mudumba · Alexandre de Brébisson · Jose Sotelo · Dendi A Suhubdy · Vincent Michalski · Joelle Pineau · Yoshua Bengio -
2017 Poster: GibbsNet: Iterative Adversarial Inference for Deep Graphical Models »
Alex Lamb · R Devon Hjelm · Yaroslav Ganin · Joseph Paul Cohen · Aaron Courville · Yoshua Bengio -
2017 Poster: Plan, Attend, Generate: Planning for Sequence-to-Sequence Models »
Caglar Gulcehre · Francis Dutil · Adam Trischler · Yoshua Bengio -
2017 Poster: Task-based End-to-end Model Learning in Stochastic Optimization »
Priya Donti · J. Zico Kolter · Brandon Amos -
2017 Poster: Z-Forcing: Training Stochastic Recurrent Networks »
Anirudh Goyal · Alessandro Sordoni · Marc-Alexandre Côté · Nan Rosemary Ke · Yoshua Bengio -
2016 : Yoshua Bengio – Credit assignment: beyond backpropagation »
Yoshua Bengio -
2016 : From Brains to Bits and Back Again »
Yoshua Bengio · Terrence Sejnowski · Christos H Papadimitriou · Jakob H Macke · Demis Hassabis · Alyson Fletcher · Andreas Tolias · Jascha Sohl-Dickstein · Konrad P Koerding -
2016 : Yoshua Bengio : Toward Biologically Plausible Deep Learning »
Yoshua Bengio -
2016 : Panel on "Explainable AI" (Yoshua Bengio, Alessio Lomuscio, Gary Marcus, Stephen Muggleton, Michael Witbrock) »
Yoshua Bengio · Alessio Lomuscio · Gary Marcus · Stephen H Muggleton · Michael Witbrock -
2016 : Yoshua Bengio: From Training Low Precision Neural Nets to Training Analog Continuous-Time Machines »
Yoshua Bengio -
2016 Symposium: Deep Learning Symposium »
Yoshua Bengio · Yann LeCun · Navdeep Jaitly · Roger Grosse -
2016 Poster: Architectural Complexity Measures of Recurrent Neural Networks »
Saizheng Zhang · Yuhuai Wu · Tong Che · Zhouhan Lin · Roland Memisevic · Russ Salakhutdinov · Yoshua Bengio -
2016 Poster: Professor Forcing: A New Algorithm for Training Recurrent Networks »
Alex M Lamb · Anirudh Goyal · Ying Zhang · Saizheng Zhang · Aaron Courville · Yoshua Bengio -
2016 Poster: On Multiplicative Integration with Recurrent Neural Networks »
Yuhuai Wu · Saizheng Zhang · Ying Zhang · Yoshua Bengio · Russ Salakhutdinov -
2016 Poster: Binarized Neural Networks »
Itay Hubara · Matthieu Courbariaux · Daniel Soudry · Ran El-Yaniv · Yoshua Bengio -
2016 Tutorial: Nuts and Bolts of Building Applications using Deep Learning »
Andrew Ng -
2015 : RL for DL »
Yoshua Bengio -
2015 : Learning Representations for Unsupervised and Transfer Learning »
Yoshua Bengio -
2015 Symposium: Deep Learning Symposium »
Yoshua Bengio · Marc'Aurelio Ranzato · Honglak Lee · Max Welling · Andrew Y Ng -
2015 Poster: Attention-Based Models for Speech Recognition »
Jan K Chorowski · Dzmitry Bahdanau · Dmitriy Serdyuk · Kyunghyun Cho · Yoshua Bengio -
2015 Poster: Equilibrated adaptive learning rates for non-convex optimization »
Yann Dauphin · Harm de Vries · Yoshua Bengio -
2015 Spotlight: Equilibrated adaptive learning rates for non-convex optimization »
Yann Dauphin · Harm de Vries · Yoshua Bengio -
2015 Spotlight: Attention-Based Models for Speech Recognition »
Jan K Chorowski · Dzmitry Bahdanau · Dmitriy Serdyuk · Kyunghyun Cho · Yoshua Bengio -
2015 Poster: Private Graphon Estimation for Sparse Graphs »
Christian Borgs · Jennifer Chayes · Adam Smith -
2015 Poster: A Recurrent Latent Variable Model for Sequential Data »
Junyoung Chung · Kyle Kastner · Laurent Dinh · Kratarth Goel · Aaron Courville · Yoshua Bengio -
2015 Poster: BinaryConnect: Training Deep Neural Networks with binary weights during propagations »
Matthieu Courbariaux · Yoshua Bengio · Jean-Pierre David -
2015 Tutorial: Deep Learning »
Geoffrey E Hinton · Yoshua Bengio · Yann LeCun -
2014 Workshop: Second Workshop on Transfer and Multi-Task Learning: Theory meets Practice »
Urun Dogan · Tatiana Tommasi · Yoshua Bengio · Francesco Orabona · Marius Kloft · Andres Munoz · Gunnar Rätsch · Hal Daumé III · Mehryar Mohri · Xuezhi Wang · Daniel Hernández-lobato · Song Liu · Thomas Unterthiner · Pascal Germain · Vinay P Namboodiri · Michael Goetz · Christopher Berlind · Sigurd Spieckermann · Marta Soare · Yujia Li · Vitaly Kuznetsov · Wenzhao Lian · Daniele Calandriello · Emilie Morvant -
2014 Workshop: Deep Learning and Representation Learning »
Andrew Y Ng · Yoshua Bengio · Adam Coates · Roland Memisevic · Sharanyan Chetlur · Geoffrey E Hinton · Shamim Nemati · Bryan Catanzaro · Surya Ganguli · Herbert Jaeger · Phil Blunsom · Leon Bottou · Volodymyr Mnih · Chen-Yu Lee · Rich M Schwartz -
2014 Workshop: OPT2014: Optimization for Machine Learning »
Zaid Harchaoui · Suvrit Sra · Alekh Agarwal · Martin Jaggi · Miro Dudik · Aaditya Ramdas · Jean Lasserre · Yoshua Bengio · Amir Beck -
2014 Poster: How transferable are features in deep neural networks? »
Jason Yosinski · Jeff Clune · Yoshua Bengio · Hod Lipson -
2014 Poster: Identifying and attacking the saddle point problem in high-dimensional non-convex optimization »
Yann N Dauphin · Razvan Pascanu · Caglar Gulcehre · Kyunghyun Cho · Surya Ganguli · Yoshua Bengio -
2014 Poster: Generative Adversarial Nets »
Ian Goodfellow · Jean Pouget-Abadie · Mehdi Mirza · Bing Xu · David Warde-Farley · Sherjil Ozair · Aaron Courville · Yoshua Bengio -
2014 Poster: On the Number of Linear Regions of Deep Neural Networks »
Guido F Montufar · Razvan Pascanu · Kyunghyun Cho · Yoshua Bengio -
2014 Demonstration: Neural Machine Translation »
Bart van Merriënboer · Kyunghyun Cho · Dzmitry Bahdanau · Yoshua Bengio -
2014 Oral: How transferable are features in deep neural networks? »
Jason Yosinski · Jeff Clune · Yoshua Bengio · Hod Lipson -
2014 Poster: Iterative Neural Autoregressive Distribution Estimator NADE-k »
Tapani Raiko · Yao Li · Kyunghyun Cho · Yoshua Bengio -
2013 Workshop: Deep Learning »
Yoshua Bengio · Hugo Larochelle · Russ Salakhutdinov · Tomas Mikolov · Matthew D Zeiler · David Mcallester · Nando de Freitas · Josh Tenenbaum · Jian Zhou · Volodymyr Mnih -
2013 Workshop: Output Representation Learning »
Yuhong Guo · Dale Schuurmans · Richard Zemel · Samy Bengio · Yoshua Bengio · Li Deng · Dan Roth · Kilian Q Weinberger · Jason Weston · Kihyuk Sohn · Florent Perronnin · Gabriel Synnaeve · Pablo R Strasser · julien audiffren · Carlo Ciliberto · Dan Goldwasser -
2013 Invited Talk: Belief Propagation Algorithms: From Matching Problems to Network Discovery in Cancer Genomics »
Jennifer Chayes -
2013 Poster: Multi-Prediction Deep Boltzmann Machines »
Ian Goodfellow · Mehdi Mirza · Aaron Courville · Yoshua Bengio -
2013 Poster: Generalized Denoising Auto-Encoders as Generative Models »
Yoshua Bengio · Li Yao · Guillaume Alain · Pascal Vincent -
2013 Poster: Stochastic Ratio Matching of RBMs for Sparse High-Dimensional Inputs »
Yann Dauphin · Yoshua Bengio -
2012 Workshop: Deep Learning and Unsupervised Feature Learning »
Yoshua Bengio · James Bergstra · Quoc V. Le -
2011 Workshop: Big Learning: Algorithms, Systems, and Tools for Learning at Scale »
Joseph E Gonzalez · Sameer Singh · Graham Taylor · James Bergstra · Alice Zheng · Misha Bilenko · Yucheng Low · Yoshua Bengio · Michael Franklin · Carlos Guestrin · Andrew McCallum · Alexander Smola · Michael Jordan · Sugato Basu -
2011 Workshop: Deep Learning and Unsupervised Feature Learning »
Yoshua Bengio · Adam Coates · Yann LeCun · Nicolas Le Roux · Andrew Y Ng -
2011 Oral: The Manifold Tangent Classifier »
Salah Rifai · Yann N Dauphin · Pascal Vincent · Yoshua Bengio · Xavier Muller -
2011 Poster: Shallow vs. Deep Sum-Product Networks »
Olivier Delalleau · Yoshua Bengio -
2011 Poster: The Manifold Tangent Classifier »
Salah Rifai · Yann N Dauphin · Pascal Vincent · Yoshua Bengio · Xavier Muller -
2011 Poster: Algorithms for Hyper-Parameter Optimization »
James Bergstra · Rémi Bardenet · Yoshua Bengio · Balázs Kégl -
2011 Poster: On Tracking The Partition Function »
Guillaume Desjardins · Aaron Courville · Yoshua Bengio -
2010 Workshop: Deep Learning and Unsupervised Feature Learning »
Honglak Lee · Marc'Aurelio Ranzato · Yoshua Bengio · Geoffrey E Hinton · Yann LeCun · Andrew Y Ng -
2009 Poster: Slow, Decorrelated Features for Pretraining Complex Cell-like Networks »
James Bergstra · Yoshua Bengio -
2009 Poster: An Infinite Factor Model Hierarchy Via a Noisy-Or Mechanism »
Aaron Courville · Douglas Eck · Yoshua Bengio -
2009 Session: Debate on Future Publication Models for the NIPS Community »
Yoshua Bengio -
2007 Poster: Augmented Functional Time Series Representation and Forecasting with Gaussian Processes »
Nicolas Chapados · Yoshua Bengio -
2007 Poster: Learning the 2-D Topology of Images »
Nicolas Le Roux · Yoshua Bengio · Pascal Lamblin · Marc Joliveau · Balázs Kégl -
2007 Spotlight: Augmented Functional Time Series Representation and Forecasting with Gaussian Processes »
Nicolas Chapados · Yoshua Bengio -
2007 Poster: Topmoumoute Online Natural Gradient Algorithm »
Nicolas Le Roux · Pierre-Antoine Manzagol · Yoshua Bengio -
2006 Poster: Greedy Layer-Wise Training of Deep Networks »
Yoshua Bengio · Pascal Lamblin · Dan Popovici · Hugo Larochelle -
2006 Talk: Greedy Layer-Wise Training of Deep Networks »
Yoshua Bengio · Pascal Lamblin · Dan Popovici · Hugo Larochelle