NeurIPS 2020

The MIT-IBM Watson AI Lab proudly presents 31 papers accepted at the 2020 Neural Information and Processing Systems conference.

NeurIPS is one of the top peer-review publication venues in the field of artificial intelligence. The 2020 NeurIPS conference had a 20% acceptance rate on papers, with only 3% receiving spotlights and 1% receiving oral presentations. Please find a schedule of presentations as well as a link to each paper below.

Oral Presentations

Click the time to see the event listing: click the title to see the paper.

12/07/2020 21:00-21:10 (EST)
Learning Physical Graph Representations from Visual Scenes Daniel Bear, Chaofei Fan, Damian Mrowca, Yunzhu Li, Seth Alter, Aran Nayebi, Jeremy Schwartz, Li Fei-Fei, Jiajun Wu, Josh Tenenbaum, Daniel Yamins

Spotlight Papers

Click the time to see the event listing: click the title to see the paper.


22:00-22:10 (EST)
Simulating a Primate Visual Cortex at the Front of CNNs Improves Robustness to Adversarial Attacks and Image Corruptions Joel Dapello, Tiago Marques, Martin Schrimpf, Frabziska Geiger, David Cox, James DiCarlo
12/07/2020 23:00-23:10 (EST) Debiased Contrastive Learning Ching-Yao Chuang, Joshua Robinson, Yen-Chen Lin, Antonio Torralba, Stefanie Jegelka
12/08/2020 11:10-11:20 (EST)
Higher-Order Certification For Randomized Smoothing Jeet Mohapatra, Ching-Yun Ko, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel
11:00-11:10 (EST)
Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms Guy Bresler, Prateek Jain, Dheeraj Nagaraj, Praneeth Netrapalli, Xian Wu
12/09/2020 11:00-11:10 (EST)
Training Stronger Baselines for Learning to Optimize Tianlong Chen, Weiyi Zhang, Zhou Jiangyang, Shiyu Chang, Sijia Liu, Lisa Amini, Zhangyang Wang
11:30-11:40 (EST)
Testing Determinantal Point Processes Khashayar Gamitry, Maryam Aliakbarpour, Stefanie Jegelka
12/10/2020 23:00-23:10 (EST)
MCUNet: Tiny Deep Learning on IoT Devices Ji Lin, Wei-Ming Chen, Yujun Lin, John Cohn, Chuang Gan, Song Han


Click the time to see the event listing: click the title to see the paper.
12/08/2020 12:00-14:00 (EST) The Lottery Ticket Hypothesis for Pre-trained BERT Networks Tianlong Chen, Johnathan Frankle, Shiyu Chang, Sijia Liu, Yang Zhang, Zhangyang Wang, Michael Carbin
12/08/2020 12:00-14:00 (EST) Learning Restricted Boltzmann Machines With Sparse Latent Variables Guy Bresler, Rares-Darius Buhai
12/08/2020 12:00-14:00 (EST) Fairness in Streaming Submodular Maximization: Algorithms and Hardness Marwa El Halabi, Slobodan Mitrovic, Ashkan Norouzi-Fard, Jakab Tardos, Jakub Tarnawski
12/08/2020 12:00-14:00 (EST) Revisiting the Sample Complexity of Sparse Spectrum Approximation of Gaussian Processes Minh Hoang, Nghia Hoang, Hai Pham,· David Woodruff
12/08/2020 12:00-14:00 (EST) CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models Vijil Chenthamarakshan, Payel Das, Samuel Hoffman, Hendrik Strobelt, Inkit Padhi, Kar Wai Lim, Benjamin Hoover, Matteo Manica, Jannis Born, Teodoro Laino, Aleksandra Mojsilovic
12/09/2020 12:00-14:00 (EST) Auxiliary Task Reweighting for Minimum-data Learning Baifeng Shi, Judy Hoffman, Kate Saenko, Trevor Darrell, Huijuan Xu
12/09/2020 12:00-14:00 (EST) Causal Discovery from Soft Interventions with Unknown Targets: Characterization and Learning Amin Jaber, Murat Kocaoglu, Karthikeyan Shanmugam, Elias Bareinboim
12/09/2020 12:00-14:00 (EST) Applications of Common Entropy in Causal Inference Murat Kocaoglu, Sanjay Shakkottai, Alexandros Dimakis, Constantine Caramanis, Sriram Vishwanath
12/09/2020 12:00-14:00 (EST) Entropic Causal Inference: Identifiability and Finite Sample Results Spencer Compton, Murat Kocaoglu, Kristjan Greenewald, Dmitriy Katz
12/09/2020 12:00-14:00 (EST) Continuous Regularized Wasserstein Barycenters Lingxiao Li, Aude Genevay, Mikhail Yurochkin, Justin M Solomon
12/09/2020 12:00-14:00 (EST) Universal Domain Adaptation through Self Supervision Kuniaki Saito, Donghyun Kim, Stan Sclaroff, Kate Saenko
12/09/2020 12:00-14:00 (EST) Approximate Cross-Validation for Structured Models Soumya Ghosh, William Stephenson, Tin Nguyen, Sameer Deshpande, Tamara Broderick
12/09/2020 12:00-14:00 (EST) AdaShare: Learning What To Share For Efficient Deep Multi-Task Learning Ximeng Sun, Rameswar Panda, Rogerio Feris, Kate Saenko
12/09/2020 12:00-14:00 (EST) Uncertainty-Aware Learning for Zero-Shot Semantic Segmentation Ping Hu, Stan Sclaroff, Kate Saenko
12/09/2020 12:00-14:00 (EST) Active Structure Learning of Causal DAGs via Directed Clique Trees Chandler Squires, Sara Magliacane, Kristjan Greenewald, Dmitriy Katz, Murat Kocaoglu, Karthikeyan Shanmugam
12/09/2020 12:00-14:00 (EST) TinyTL: Reduce Memory, Not Parameters for Efficient On-Device Learning Han Cai, Chuang Gan, Ligeng Zhu, Song Han
12/10/2020 12:00-14:00 (EST) Adversarially-learned Inference via an Ensemble of Discrete Undirected Graphical Models Adarsh K Jeewajee, Leslie Kaelbling
12/10/2020 12:00-14:00 (EST Asymptotic Guarantees for Generative Modeling based on the Smooth Wasserstein Distance Ziv Goldfeld, Kristjan Greenewald, Kengo Kato
12/10/2020 12:00-14:00 (EST) Online Bayesian Goal Inference for Boundedly-Rational Planning Agents Tan Zhi-Xuan, Jordyn Mann, Tom Silver, Josh Tenenbaum, Vikash Mansinghka
12/10/2020 12:00-14:00 (EST) Log-Likelihood Ratio Minimizing Flows: Towards Robust and Quantifiable Neural Distribution Alignment Ben Usman, Avneesh Sud, Nick Dufour, Kate Saenko
12/10/2020 12:00-14:00 (EST) Sharp Representation Theorems for ReLU Networks with Precise Dependence on Depth Guy Bresler, Dheeraj Nagaraj
12/10/2020 12:00-14:00 (EST) Robust Federated Learning: The Case of Affine Distribution Shifts Amirhossein Reisizadeh, Farzan Farnia, Ramtin Pedarsani, Ali Jadbabaie
12/10/2020 12:00-14:00 (EST) Differentiable Augmentation for Data-Efficient GAN Training Shengyu Zhao, Zhijian Liu, Ji Lin, Jun-Yan Zhu, Song Han