More from the Same Authors

• 2021 : An Extensible Benchmark Suite for Learning to Simulate Physical Systems »
  Karl Otness · Arvi Gjoka · Joan Bruna · Daniele Panozzo · Benjamin Peherstorfer · Teseo Schneider · Denis Zorin
• 2021 Spotlight: Offline RL Without Off-Policy Evaluation »
  David Brandfonbrener · Will Whitney · Rajesh Ranganath · Joan Bruna
• 2021 : Quantile Filtered Imitation Learning »
  David Brandfonbrener · Will Whitney · Rajesh Ranganath · Joan Bruna
• 2022 : Score-based Seismic Inverse Problems »
  Sriram Ravula · Dimitri Voytan · Elad Liebman · Ram Tuvi · Yash Gandhi · Hamza Ghani · Alex Ardel · Mrinal Sen · Alex Dimakis
• 2022 : Investigating Reproducibility from the Decision Boundary Perspective. »
  Gowthami Somepalli · Arpit Bansal · Liam Fowl · Ping-yeh Chiang · Yehuda Dar · Richard Baraniuk · Micah Goldblum · Tom Goldstein
• 2022 : Using quadratic equations for overparametrized models »
  Shuang Li · William Swartworth · Martin Takac · Deanna Needell · Robert Gower
• 2022 : Retrieval-based Controllable Molecule Generation »
  Jack Wang · Weili Nie · Zhuoran Qiao · Chaowei Xiao · Richard Baraniuk · Anima Anandkumar
• 2022 : HotProtein: A Novel Framework for Protein Thermostability Prediction and Editing »
  Tianlong Chen · Chengyue Gong · Daniel Diaz · Xuxi Chen · Jordan Wells · Qiang Liu · Zhangyang Wang · Andrew Ellington · Alex Dimakis · Adam Klivans
• 2022 : Exact Visualization of Deep Neural Network Geometry and Decision Boundary »
  Ahmed Imtiaz Humayun · Randall Balestriero · Richard Baraniuk
• 2022 : Discovering the Hidden Vocabulary of DALLE-2 »
  Giannis Daras · Alex Dimakis
• 2022 : Multiresolution Textual Inversion »
  Giannis Daras · Alex Dimakis
• 2022 : Using Deep Learning and Macroscopic Imaging of Porcine Heart Valve Leaflets to Predict Uniaxial Stress-Strain Responses »
  Luis Victor · CJ Barberan · Richard Baraniuk · Jane Grande-Allen
• 2023 Workshop: Learning-Based Solutions for Inverse Problems »
  Shirin Jalali · christopher metzler · Ajil Jalal · Jon Tamir · Reinhard Heckel · Paul Hand · Arian Maleki · Richard Baraniuk
• 2022 Poster: Exponential Separations in Symmetric Neural Networks »
  Aaron Zweig · Joan Bruna
• 2022 Poster: When does return-conditioned supervised learning work for offline reinforcement learning? »
  David Brandfonbrener · Alberto Bietti · Jacob Buckman · Romain Laroche · Joan Bruna
• 2022 Poster: Multitasking Models are Robust to Structural Failure: A Neural Model for Bilingual Cognitive Reserve »
  Giannis Daras · Negin Raoof · Zoi Gkalitsiou · Alex Dimakis
• 2022 Poster: Zonotope Domains for Lagrangian Neural Network Verification »
  Matt Jordan · Jonathan Hayase · Alex Dimakis · Sewoong Oh
• 2022 Poster: On Non-Linear operators for Geometric Deep Learning »
  Grégoire Sergeant-Perthuis · Jakob Maier · Joan Bruna · Edouard Oyallon
• 2022 Poster: Online Nonnegative CP-dictionary Learning for Markovian Data »
  Hanbaek Lyu · Christopher Strohmeier · Deanna Needell
• 2022 Poster: Parameters or Privacy: A Provable Tradeoff Between Overparameterization and Membership Inference »
  Jasper Tan · Blake Mason · Hamid Javadi · Richard Baraniuk
• 2022 Poster: Learning single-index models with shallow neural networks »
  Alberto Bietti · Joan Bruna · Clayton Sanford · Min Jae Song
• 2021 : Alex Dimakis Talk »
  Alex Dimakis
• 2021 Workshop: Workshop on Deep Learning and Inverse Problems »
  Reinhard Heckel · Paul Hand · Rebecca Willett · christopher metzler · Mahdi Soltanolkotabi
• 2021 Poster: On the Sample Complexity of Learning under Geometric Stability »
  Alberto Bietti · Luca Venturi · Joan Bruna
• 2021 Poster: Inverse Problems Leveraging Pre-trained Contrastive Representations »
  Sriram Ravula · Georgios Smyrnis · Matt Jordan · Alex Dimakis
• 2021 Poster: The Flip Side of the Reweighted Coin: Duality of Adaptive Dropout and Regularization »
  Daniel LeJeune · Hamid Javadi · Richard Baraniuk
• 2021 Poster: Robust Compressed Sensing MRI with Deep Generative Priors »
  Ajil Jalal · Marius Arvinte · Giannis Daras · Eric Price · Alex Dimakis · Jon Tamir
• 2021 Poster: On the Cryptographic Hardness of Learning Single Periodic Neurons »
  Min Jae Song · Ilias Zadik · Joan Bruna
• 2021 Poster: Score-based Generative Neural Networks for Large-Scale Optimal Transport »
  Grady Daniels · Tyler Maunu · Paul Hand
• 2021 Poster: Offline RL Without Off-Policy Evaluation »
  David Brandfonbrener · Will Whitney · Rajesh Ranganath · Joan Bruna
• 2020 : Invited speaker: Online nonnegative matrix factorization for Markovian and other real data, Deanna Needell and Hanbaek Lyu »
  Hanbake Lyu · Deanna Needell
• 2020 : Opening Remarks »
  Reinhard Heckel · Paul Hand · Soheil Feizi · Lenka Zdeborová · Richard Baraniuk
• 2020 Workshop: Workshop on Deep Learning and Inverse Problems »
  Reinhard Heckel · Paul Hand · Richard Baraniuk · Lenka Zdeborová · Soheil Feizi
• 2020 : Newcomer presentation »
  Reinhard Heckel · Paul Hand
• 2020 Poster: A mean-field analysis of two-player zero-sum games »
  Carles Domingo-Enrich · Samy Jelassi · Arthur Mensch · Grant Rotskoff · Joan Bruna
• 2020 Poster: Can Graph Neural Networks Count Substructures? »
  Zhengdao Chen · Lei Chen · Soledad Villar · Joan Bruna
• 2020 Poster: Analytical Probability Distributions and Exact Expectation-Maximization for Deep Generative Networks »
  Randall Balestriero · Sebastien PARIS · Richard Baraniuk
• 2020 Poster: SMYRF - Efficient Attention using Asymmetric Clustering »
  Giannis Daras · Nikita Kitaev · Augustus Odena · Alex Dimakis
• 2020 Session: Orals & Spotlights Track 26: Graph/Relational/Theory »
  Joan Bruna · Cassio de Campos
• 2020 Poster: MomentumRNN: Integrating Momentum into Recurrent Neural Networks »
  Tan Nguyen · Richard Baraniuk · Andrea Bertozzi · Stanley Osher · Bao Wang
• 2020 Poster: IDEAL: Inexact DEcentralized Accelerated Augmented Lagrangian Method »
  Yossi Arjevani · Joan Bruna · Bugra Can · Mert Gurbuzbalaban · Stefanie Jegelka · Hongzhou Lin
• 2020 Poster: Applications of Common Entropy for Causal Inference »
  Murat Kocaoglu · Sanjay Shakkottai · Alex Dimakis · Constantine Caramanis · Sriram Vishwanath
• 2020 Spotlight: IDEAL: Inexact DEcentralized Accelerated Augmented Lagrangian Method »
  Yossi Arjevani · Joan Bruna · Bugra Can · Mert Gurbuzbalaban · Stefanie Jegelka · Hongzhou Lin
• 2020 Poster: Exactly Computing the Local Lipschitz Constant of ReLU Networks »
  Matt Jordan · Alex Dimakis
• 2020 Poster: Nonasymptotic Guarantees for Spiked Matrix Recovery with Generative Priors »
  Jorio Cocola · Paul Hand · Vlad Voroninski
• 2020 Poster: A Dynamical Central Limit Theorem for Shallow Neural Networks »
  Zhengdao Chen · Grant Rotskoff · Joan Bruna · Eric Vanden-Eijnden
• 2020 Poster: Robust compressed sensing using generative models »
  Ajil Jalal · Liu Liu · Alex Dimakis · Constantine Caramanis
• 2019 : Poster Session »
  Pravish Sainath · Mohamed Akrout · Charles Delahunt · Nathan Kutz · Guangyu Robert Yang · Joseph Marino · L F Abbott · Nicolas Vecoven · Damien Ernst · andrew warrington · Michael Kagan · Kyunghyun Cho · Kameron Harris · Leopold Grinberg · John J. Hopfield · Dmitry Krotov · Taliah Muhammad · Erick Cobos · Edgar Walker · Jacob Reimer · Andreas Tolias · Alexander Ecker · Janaki Sheth · Yu Zhang · Maciej Wołczyk · Jacek Tabor · Szymon Maszke · Roman Pogodin · Dane Corneil · Wulfram Gerstner · Baihan Lin · Guillermo Cecchi · Jenna M Reinen · Irina Rish · Guillaume Bellec · Darjan Salaj · Anand Subramoney · Wolfgang Maass · Yueqi Wang · Ari Pakman · Jin Hyung Lee · Liam Paninski · Bryan Tripp · Colin Graber · Alex Schwing · Luke Prince · Gabriel Ocker · Michael Buice · Benjamin Lansdell · Konrad Kording · Jack Lindsey · Terrence Sejnowski · Matthew Farrell · Eric Shea-Brown · Nicolas Farrugia · Victor Nepveu · Jiwoong Im · Kristin Branson · Brian Hu · Ramakrishnan Iyer · Stefan Mihalas · Sneha Aenugu · Hananel Hazan · Sihui Dai · Tan Nguyen · Doris Tsao · Richard Baraniuk · Anima Anandkumar · Hidenori Tanaka · Aran Nayebi · Stephen Baccus · Surya Ganguli · Dean Pospisil · Eilif Muller · Jeffrey S Cheng · Gaël Varoquaux · Kamalaker Dadi · Dimitrios C Gklezakos · Rajesh PN Rao · Anand Louis · Christos Papadimitriou · Santosh Vempala · Naganand Yadati · Daniel Zdeblick · Daniela M Witten · Nicholas Roberts · Vinay Prabhu · Pierre Bellec · Poornima Ramesh · Jakob H Macke · Santiago Cadena · Guillaume Bellec · Franz Scherr · Owen Marschall · Robert Kim · Hannes Rapp · Marcio Fonseca · Oliver Armitage · Jiwoong Im · Thomas Hardcastle · Abhishek Sharma · Wyeth Bair · Adrian Valente · Shane Shang · Merav Stern · Rutuja Patil · Peter Wang · Sruthi Gorantla · Peter Stratton · Tristan Edwards · Jialin Lu · Martin Ester · Yurii Vlasov · Siavash Golkar
• 2019 : Poster and Coffee Break 1 »
  Aaron Sidford · Aditya Mahajan · Alejandro Ribeiro · Alex Lewandowski · Ali H Sayed · Ambuj Tewari · Angelika Steger · Anima Anandkumar · Asier Mujika · Hilbert J Kappen · Bolei Zhou · Byron Boots · Chelsea Finn · Chen-Yu Wei · Chi Jin · Ching-An Cheng · Christina Yu · Clement Gehring · Craig Boutilier · Dahua Lin · Daniel McNamee · Daniel Russo · David Brandfonbrener · Denny Zhou · Devesh Jha · Diego Romeres · Doina Precup · Dominik Thalmeier · Eduard Gorbunov · Elad Hazan · Elena Smirnova · Elvis Dohmatob · Emma Brunskill · Enrique Munoz de Cote · Ethan Waldie · Florian Meier · Florian Schaefer · Ge Liu · Gergely Neu · Haim Kaplan · Hao Sun · Hengshuai Yao · Jalaj Bhandari · James A Preiss · Jayakumar Subramanian · Jiajin Li · Jieping Ye · Jimmy Smith · Joan Bas Serrano · Joan Bruna · John Langford · Jonathan Lee · Jose A. Arjona-Medina · Kaiqing Zhang · Karan Singh · Yuping Luo · Zafarali Ahmed · Zaiwei Chen · Zhaoran Wang · Zhizhong Li · Zhuoran Yang · Ziping Xu · Ziyang Tang · Yi Mao · David Brandfonbrener · Shirli Di-Castro · Riashat Islam · Zuyue Fu · Abhishek Naik · Saurabh Kumar · Benjamin Petit · Angeliki Kamoutsi · Simone Totaro · Arvind Raghunathan · Rui Wu · Donghwan Lee · Dongsheng Ding · Alec Koppel · Hao Sun · Christian Tjandraatmadja · Mahdi Karami · Jincheng Mei · Chenjun Xiao · Junfeng Wen · Zichen Zhang · Ross Goroshin · Mohammad Pezeshki · Jiaqi Zhai · Philip Amortila · Shuo Huang · Mariya Vasileva · El houcine Bergou · Adel Ahmadyan · Haoran Sun · Sheng Zhang · Lukas Gruber · Yuanhao Wang · Tetiana Parshakova
• 2019 : Surya Ganguli, Yasaman Bahri, Florent Krzakala moderated by Lenka Zdeborova »
  Florent Krzakala · Yasaman Bahri · Surya Ganguli · Lenka Zdeborová · Adji Bousso Dieng · Joan Bruna
• 2019 : Poster Spotlight 1 »
  David Brandfonbrener · Joan Bruna · Tom Zahavy · Haim Kaplan · Yishay Mansour · Nikos Karampatziakis · John Langford · Paul Mineiro · Donghwan Lee · Niao He
• 2019 Workshop: Information Theory and Machine Learning »
  Shengjia Zhao · Jiaming Song · Yanjun Han · Kristy Choi · Pratyusha Kalluri · Ben Poole · Alex Dimakis · Jiantao Jiao · Tsachy Weissman · Stefano Ermon
• 2019 Workshop: Solving inverse problems with deep networks: New architectures, theoretical foundations, and applications »
  Reinhard Heckel · Paul Hand · Richard Baraniuk · Joan Bruna · Alex Dimakis · Deanna Needell
• 2019 Poster: Gradient Dynamics of Shallow Univariate ReLU Networks »
  Francis Williams · Matthew Trager · Daniele Panozzo · Claudio Silva · Denis Zorin · Joan Bruna
• 2019 Poster: On the Expressive Power of Deep Polynomial Neural Networks »
  Joe Kileel · Matthew Trager · Joan Bruna
• 2019 Poster: Global Guarantees for Blind Demodulation with Generative Priors »
  Paul Hand · Babhru Joshi
• 2019 Poster: Inverting Deep Generative models, One layer at a time »
  Qi Lei · Ajil Jalal · Inderjit Dhillon · Alex Dimakis
• 2019 Poster: Finding the Needle in the Haystack with Convolutions: on the benefits of architectural bias »
  Stéphane d'Ascoli · Levent Sagun · Giulio Biroli · Joan Bruna
• 2019 Poster: Provable Certificates for Adversarial Examples: Fitting a Ball in the Union of Polytopes »
  Matt Jordan · Justin Lewis · Alex Dimakis
• 2019 Poster: Primal-Dual Block Generalized Frank-Wolfe »
  Qi Lei · JIACHENG ZHUO · Constantine Caramanis · Inderjit Dhillon · Alex Dimakis
• 2019 Poster: On the equivalence between graph isomorphism testing and function approximation with GNNs »
  Zhengdao Chen · Soledad Villar · Lei Chen · Joan Bruna
• 2019 Poster: Sparse Logistic Regression Learns All Discrete Pairwise Graphical Models »
  Shanshan Wu · Sujay Sanghavi · Alex Dimakis
• 2019 Spotlight: Sparse Logistic Regression Learns All Discrete Pairwise Graphical Models »
  Shanshan Wu · Sujay Sanghavi · Alex Dimakis
• 2019 Poster: Stability of Graph Scattering Transforms »
  Fernando Gama · Alejandro Ribeiro · Joan Bruna
• 2019 Poster: Learning Distributions Generated by One-Layer ReLU Networks »
  Shanshan Wu · Alex Dimakis · Sujay Sanghavi
• 2019 Poster: The Geometry of Deep Networks: Power Diagram Subdivision »
  Randall Balestriero · Romain Cosentino · Behnaam Aazhang · Richard Baraniuk
• 2018 : Invited Talk 3 »
  Joan Bruna
• 2018 Workshop: Integration of Deep Learning Theories »
  Richard Baraniuk · Anima Anandkumar · Stephane Mallat · Ankit Patel · nhật Hồ
• 2018 : Panel Discussion »
  Richard Baraniuk · Maarten V. de Hoop · Paul A Johnson
• 2018 : Joan Bruna »
  Joan Bruna
• 2018 : Introduction »
  Laura Pyrak-Nolte · James Rustad · Richard Baraniuk
• 2018 Workshop: Machine Learning for Geophysical & Geochemical Signals »
  Laura Pyrak-Nolte · James Rustad · Richard Baraniuk
• 2018 Poster: A convex program for bilinear inversion of sparse vectors »
  Alireza Aghasi · Ali Ahmed · Paul Hand · Babhru Joshi
• 2018 Poster: Experimental Design for Cost-Aware Learning of Causal Graphs »
  Erik Lindgren · Murat Kocaoglu · Alex Dimakis · Sriram Vishwanath
• 2018 Poster: Blind Deconvolutional Phase Retrieval via Convex Programming »
  Ali Ahmed · Alireza Aghasi · Paul Hand
• 2018 Spotlight: Blind Deconvolutional Phase Retrieval via Convex Programming »
  Ali Ahmed · Alireza Aghasi · Paul Hand
• 2018 Poster: Phase Retrieval Under a Generative Prior »
  Paul Hand · Oscar Leong · Vlad Voroninski
• 2018 Oral: Phase Retrieval Under a Generative Prior »
  Paul Hand · Oscar Leong · Vlad Voroninski
• 2017 Workshop: NIPS Highlights (MLTrain), Learn How to code a paper with state of the art frameworks »
  Alex Dimakis · Nikolaos Vasiloglou · Guy Van den Broeck · Alexander Ihler · Assaf Araki
• 2017 Workshop: Advances in Modeling and Learning Interactions from Complex Data »
  Gautam Dasarathy · Mladen Kolar · Richard Baraniuk
• 2017 Poster: Streaming Weak Submodularity: Interpreting Neural Networks on the Fly »
  Ethan Elenberg · Alex Dimakis · Moran Feldman · Amin Karbasi
• 2017 Oral: Streaming Weak Submodularity: Interpreting Neural Networks on the Fly »
  Ethan Elenberg · Alex Dimakis · Moran Feldman · Amin Karbasi
• 2017 Poster: Learned D-AMP: Principled Neural Network based Compressive Image Recovery »
  Chris Metzler · Ali Mousavi · Richard Baraniuk
• 2017 Poster: Model-Powered Conditional Independence Test »
  Rajat Sen · Ananda Theertha Suresh · Karthikeyan Shanmugam · Alex Dimakis · Sanjay Shakkottai
• 2017 Tutorial: Geometric Deep Learning on Graphs and Manifolds »
  Michael Bronstein · Joan Bruna · arthur szlam · Xavier Bresson · Yann LeCun
• 2016 Workshop: Machine Learning for Education »
  Richard Baraniuk · Jiquan Ngiam · Christoph Studer · Phillip Grimaldi · Andrew Lan
• 2016 Poster: Leveraging Sparsity for Efficient Submodular Data Summarization »
  Erik Lindgren · Shanshan Wu · Alex Dimakis
• 2016 Poster: A Probabilistic Framework for Deep Learning »
  Ankit Patel · Tan Nguyen · Richard Baraniuk
• 2016 Poster: Single Pass PCA of Matrix Products »
  Shanshan Wu · Srinadh Bhojanapalli · Sujay Sanghavi · Alex Dimakis
• 2015 : Low-dimensional inference with high-dimensional data »
  Richard Baraniuk
• 2015 : Probabilistic Theory of Deep Learning »
  Richard Baraniuk
• 2015 Poster: Orthogonal NMF through Subspace Exploration »
  Megasthenis Asteris · Dimitris Papailiopoulos · Alex Dimakis
• 2015 Poster: Sparse PCA via Bipartite Matchings »
  Megasthenis Asteris · Dimitris Papailiopoulos · Anastasios Kyrillidis · Alex Dimakis
• 2015 Poster: Learning Causal Graphs with Small Interventions »
  Karthikeyan Shanmugam · Murat Kocaoglu · Alex Dimakis · Sriram Vishwanath
• 2014 Workshop: Human Propelled Machine Learning »
  Richard Baraniuk · Michael Mozer · Divyanshu Vats · Christoph Studer · Andrew E Waters · Andrew Lan
• 2014 Poster: Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation »
  Emily Denton · Wojciech Zaremba · Joan Bruna · Yann LeCun · Rob Fergus
• 2014 Poster: Sparse Polynomial Learning and Graph Sketching »
  Murat Kocaoglu · Karthikeyan Shanmugam · Alex Dimakis · Adam Klivans
• 2014 Poster: On the Information Theoretic Limits of Learning Ising Models »
  Rashish Tandon · Karthikeyan Shanmugam · Pradeep Ravikumar · Alex Dimakis
• 2014 Oral: Sparse Polynomial Learning and Graph Sketching »
  Murat Kocaoglu · Karthikeyan Shanmugam · Alex Dimakis · Adam Klivans
• 2013 Poster: When in Doubt, SWAP: High-Dimensional Sparse Recovery from Correlated Measurements »
  Divyanshu Vats · Richard Baraniuk
• 2011 Poster: SpaRCS: Recovering low-rank and sparse matrices from compressive measurements »
  Andrew E Waters · Aswin C Sankaranarayanan · Richard Baraniuk
• 2009 Workshop: Manifolds, sparsity, and structured models: When can low-dimensional geometry really help? »
  Richard Baraniuk · Volkan Cevher · Mark A Davenport · Piotr Indyk · Bruno Olshausen · Michael B Wakin
• 2008 Poster: Sparse Signal Recovery Using Markov Random Fields »
  Volkan Cevher · Marco F Duarte · Chinmay Hegde · Richard Baraniuk
• 2008 Spotlight: Sparse Signal Recovery Using Markov Random Fields »
  Volkan Cevher · Marco F Duarte · Chinmay Hegde · Richard Baraniuk
• 2007 Poster: Random Projections for Manifold Learning »
  Chinmay Hegde · Richard Baraniuk