Timezone: »
Author Information
Yoshua Bengio (Mila - University of Montreal)
Carla Gomes (Cornell University)
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.
Jeff Dean (Google Research)
Jeff joined Google in 1999 and is currently a Google Senior Fellow. He currently leads Google's Research and Health divisions, where he co-founded the Google Brain team. He has co-designed/implemented multiple generations of Google's distributed machine learning systems for neural network training and inference, as well as multiple generations of Google's crawling, indexing, and query serving systems, and major pieces of Google's initial advertising and AdSense for Content systems. He is also a co-designer and co-implementor of Google's distributed computing infrastructure, including the MapReduce, BigTable and Spanner systems, protocol buffers, LevelDB, systems infrastructure for statistical machine translation, and a variety of internal and external libraries and developer tools. He received a Ph.D. in Computer Science from the University of Washington in 1996, working with Craig Chambers on compiler techniques for object-oriented languages. He is a Fellow of the ACM, a Fellow of the AAAS, a member of the U.S. National Academy of Engineering, and a recipient of the Mark Weiser Award and the ACM Prize in Computing.
Lester Mackey (Stanford)
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 : Gaussian Mixture Variational Autoencoder with Contrastive Learning for Multi-Label Classification »
Junwen Bai · Shufeng Kong · Carla Gomes -
2021 : Gaussian Mixture Variational Autoencoder with Contrastive Learning for Multi-Label Classification »
Junwen Bai · Shufeng Kong · Carla Gomes -
2021 : Resolving Super Fine-Resolution SIF via Coarsely-Supervised U-Net Regression »
Joshua Fan · Di Chen · Jiaming Wen · Ying Sun · Carla Gomes -
2021 : A GNN-RNN Approach for Harnessing Geospatial and Temporal Information: Application to Crop Yield Prediction »
Joshua Fan · Junwen Bai · Zhiyun Li · Ariel Ortiz-Bobea · Carla Gomes -
2022 : Xtal2DoS: Attention-based Crystal to Sequence Learning for Density of States Prediction »
Junwen Bai · Yuanqi Du · Yingheng Wang · Shufeng Kong · John Gregoire · Carla Gomes -
2022 : Structure-based Drug Design with Equivariant Diffusion Models »
Arne Schneuing · Yuanqi Du · Charles Harris · Arian Jamasb · Ilia Igashov · weitao Du · Tom Blundell · Pietro Lió · Carla Gomes · Max Welling · Michael Bronstein · Bruno Correia -
2022 : Adaptive Bias Correction for Improved Subseasonal Forecast »
Soukayna Mouatadid · Paulo Orenstein · Genevieve Flaspohler · Judah Cohen · Miruna Oprescu · Ernest Fraenkel · Lester Mackey -
2023 Poster: Unsupervised Learning for Solving the Travelling Salesman Problem »
Yimeng Min · Yiwei Bai · Carla Gomes -
2023 Poster: A new perspective on building efficient and expressive 3D equivariant graph neural networks »
weitao Du · Yuanqi Du · Limei Wang · Dieqiao Feng · Guifeng Wang · Shuiwang Ji · Carla Gomes · Zhi-Ming Ma -
2023 Poster: M$^2$Hub: Unlocking the Potential of Machine Learning for Materials Discovery »
Yuanqi Du · Yingheng Wang · Yining Huang · Jianan Canal Li · Yanqiao Zhu · Tian Xie · Chenru Duan · John Gregoire · Carla Gomes -
2023 Workshop: AI for Science: from Theory to Practice »
Yuanqi Du · Max Welling · Yoshua Bengio · Marinka Zitnik · Carla Gomes · Jure Leskovec · Maria Brbic · Wenhao Gao · Kexin Huang · Ziming Liu · Rocío Mercado · Miles Cranmer · Shengchao Liu · Lijing Wang -
2022 : Adaptive Bias Correction for Improved Subseasonal Forecast »
Soukayna Mouatadid · Paulo Orenstein · Genevieve Flaspohler · Judah Cohen · Miruna Oprescu · Ernest Fraenkel · Lester Mackey -
2022 : Jeff Dean - Invited Talk »
Jeff Dean -
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: Left Heavy Tails and the Effectiveness of the Policy and Value Networks in DNN-based best-first search for Sokoban Planning »
Dieqiao Feng · Carla Gomes · Bart Selman -
2021 : A GNN-RNN Approach for Harnessing Geospatial and Temporal Information: Application to Crop Yield Prediction »
Joshua Fan · Junwen Bai · Zhiyun Li · Ariel Ortiz-Bobea · Carla Gomes -
2021 : Resolving Super Fine-Resolution SIF via Coarsely-Supervised U-Net Regression »
Joshua Fan · Di Chen · Jiaming Wen · Ying Sun · Carla Gomes -
2021 Poster: Towards Deeper Deep Reinforcement Learning with Spectral Normalization »
Nils Bjorck · Carla Gomes · Kilian Weinberger -
2021 Poster: Contrastively Disentangled Sequential Variational Autoencoder »
Junwen Bai · Weiran Wang · Carla Gomes -
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 : Andrew Ng: Practical limitations of today's deep learning in healthcare »
Andrew Ng -
2020 Poster: A Novel Automated Curriculum Strategy to Solve Hard Sokoban Planning Instances »
Dieqiao Feng · Carla Gomes · Bart Selman -
2019 : AI and Sustainable Development »
Fei Fang · Carla Gomes · Miguel Luengo-Oroz · Thomas Dietterich · Julien Cornebise -
2019 : Lester Mackey (Microsoft Research and Stanford) »
Lester Mackey -
2019 : Carla Gomes (Cornell) »
Carla Gomes -
2019 : Invited Speaker: Jeff Dean »
Jeff Dean -
2019 : Jeff Dean (Google AI) »
Jeff Dean -
2019 : Computational Sustainability: Computing for a Better World and a Sustainable Future »
Carla Gomes -
2019 Workshop: Tackling Climate Change with ML »
David Rolnick · Priya Donti · Lynn Kaack · Alexandre Lacoste · Tegan Maharaj · Andrew Ng · John Platt · Jennifer Chayes · Yoshua Bengio -
2019 Poster: How to Initialize your Network? Robust Initialization for WeightNorm & ResNets »
Devansh Arpit · Víctor Campos · Yoshua Bengio -
2019 Poster: Variational Temporal Abstraction »
Taesup Kim · Sungjin Ahn · Yoshua Bengio -
2018 : Opening remarks »
Yoshua Bengio -
2018 Poster: Image-to-image translation for cross-domain disentanglement »
Abel Gonzalez-Garcia · Joost van de Weijer · Yoshua Bengio -
2018 Poster: Understanding Batch Normalization »
Johan Bjorck · Carla Gomes · Bart Selman · Kilian Weinberger -
2018 Poster: MetaGAN: An Adversarial Approach to Few-Shot Learning »
Ruixiang ZHANG · Tong Che · Zoubin Ghahramani · Yoshua Bengio · Yangqiu Song -
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: 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 : Future Hardware Directions »
Gregory Diamos · Jeff Dean · Simon Knowles · Michael James · Scott Gray -
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 : Invited Talk: Machine Learning for Systems and Systems for Machine Learning, Jeff Dean, Google Brain »
Jeff Dean -
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 Poster: Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net »
Anirudh Goyal · Nan Rosemary Ke · Surya Ganguli · Yoshua Bengio -
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: Z-Forcing: Training Stochastic Recurrent Networks »
Anirudh Goyal · Alessandro Sordoni · Marc-Alexandre Côté · Nan Rosemary Ke · Yoshua Bengio -
2016 : Invited Talk: Scaling Machine Learning Using TensorFlow (Jeff Dean, Google Brain) »
Jeff Dean -
2016 : Jeff Dean – TensorFlow: Future Directions for Simplifying Large-Scale Machine Learning »
Jeff Dean -
2016 Poster: Solving Marginal MAP Problems with NP Oracles and Parity Constraints »
Yexiang Xue · zhiyuan li · Stefano Ermon · Carla Gomes · Bart Selman -
2016 Tutorial: Nuts and Bolts of Building Applications using Deep Learning »
Andrew Ng -
2015 : TensorFlow: A system for machine learning on heterogeneous systems »
Jeff Dean -
2015 Poster: Measuring Sample Quality with Stein's Method »
Jackson Gorham · Lester Mackey -
2015 Spotlight: Measuring Sample Quality with Stein's Method »
Jackson Gorham · Lester Mackey -
2015 Tutorial: Large-Scale Distributed Systems for Training Neural Networks »
Jeff Dean · Oriol Vinyals -
2014 Workshop: High-energy particle physics, machine learning, and the HiggsML data challenge (HEPML) »
Glen Cowan · Balázs Kégl · Kyle Cranmer · Gábor Melis · Tim Salimans · Vladimir Vava Gligorov · Daniel Whiteson · Lester Mackey · Wojciech Kotlowski · Roberto Díaz Morales · Pierre Baldi · Cecile Germain · David Rousseau · Isabelle Guyon · Tianqi Chen -
2013 Workshop: Machine Learning for Sustainability »
Edwin Bonilla · Thomas Dietterich · Theodoros Damoulas · Andreas Krause · Daniel Sheldon · Iadine Chades · J. Zico Kolter · Bistra Dilkina · Carla Gomes · Hugo P Simao -
2013 Poster: DeViSE: A Deep Visual-Semantic Embedding Model »
Andrea Frome · Greg Corrado · Jonathon Shlens · Samy Bengio · Jeff Dean · Marc'Aurelio Ranzato · Tomas Mikolov -
2013 Poster: Distributed Representations of Words and Phrases and their Compositionality »
Tomas Mikolov · Ilya Sutskever · Kai Chen · Greg Corrado · Jeff Dean -
2013 Poster: Embed and Project: Discrete Sampling with Universal Hashing »
Stefano Ermon · Carla Gomes · Ashish Sabharwal · Bart Selman -
2012 Poster: Large Scale Distributed Deep Networks »
Jeff Dean · Greg Corrado · Rajat Monga · Kai Chen · Matthieu Devin · Quoc V Le · Mark Mao · Marc'Aurelio Ranzato · Andrew Senior · Paul Tucker · Ke Yang · Andrew Y Ng -
2012 Poster: Density Propagation and Improved Bounds on the Partition Function »
Stefano Ermon · Carla Gomes · Ashish Sabharwal · Bart Selman -
2011 Poster: Accelerated Adaptive Markov Chain for Partition Function Computation »
Stefano Ermon · Carla Gomes · Ashish Sabharwal · Bart Selman -
2011 Spotlight: Accelerated Adaptive Markov Chain for Partition Function Computation »
Stefano Ermon · Carla Gomes · Ashish Sabharwal · Bart Selman -
2006 Poster: Near-Uniform Sampling of Combinatorial Spaces Using XOR Constraints »
Carla Gomes · Ashish Sabharwal · Bart Selman