NeurIPS 2021 Accepted Papers

NeurIPS image

November 17, 2021

This year marks the 35th annual Conference on Neural Information Processing Systems (NeurIPS): a workshop and conference hosted by the Neural Information Processing Systems Foundation that celebrates the work being done in artificial intelligences and machine learning and promotes the exchange of research advances. The conference will be held virtually again this year from December 6th through December 14th. This year twelve of CAIDA's members have had papers accepted.  You can see a list of our members’ papers below, and you can find out more about this year’s conference here.


Sanae Amani · Christos Thrampoulidis

UCB-based Algorithms for Multinomial Logistic Regression Bandits

Diana Cai · Sameer Deshpande · Michael Hughes · Tamara Broderick · Trevor Campbell · Nick Foti · Barbara Engelhardt · Sinead Williamson

Your Model is Wrong: Robustness and misspecification in probabilistic modeling


Yann Dubois · Benjamin Bloem-Reddy · Karen Ullrich · Chris Maddison

Lossy Compression for Lossless Prediction


Moshe Eliasof · Eldad Haber · Eran Treister

PDE-GCN: Novel Architectures for Graph Neural Networks Motivated by Partial Differential Equations


R David Evans · Tor Aamodt

AC-GC: Lossy Activation Compression with Guaranteed Convergence


Babhru Joshi · Xiaowei Li · Yaniv Plan · Ozgur Yilmaz

PLUGIn: A simple algorithm for inverting generative models with recovery guarantees


Frederic Koehler · Lijia Zhou · Danica Sutherland · Nathan Srebro

Uniform Convergence of Interpolators: Gaussian Width, Norm Bounds and Benign Overfitting


Mingchen Li · Xuechen Zhang · Christos Thrampoulidis · Jiasi Chen · Samet Oymak

AutoBalance: Optimized Loss Functions for Imbalanced Data


Muchen Li · Leonid Sigal

Referring Transformer: A One-step Approach to Multi-task Visual Grounding


Yazhe Li · Roman Pogodin · Danica Sutherland · Arthur Gretton

Self-Supervised Learning with Kernel Dependence Maximization


Feng Liu · Wenkai Xu · Jie Lu · Danica Sutherland

Meta Two-Sample Testing: Learning Kernels for Testing with Limited Data


DOU QI · Marleen de Bruijne · Ben Glocker · Aasa Feragen · Herve Lombaert · Ipek Oguz · Jonas Teuwen · Islem Rekik · Darko Stern · Xiaoxiao Li

Medical Imaging meets NeurIPS


Tanzila Rahman · Mengyu Yang · Leonid Sigal

TriBERT: Human-centric Audio-visual Representation Learning


Ganesh Ramachandra Kini · Orestis Paraskevas · Samet Oymak · Christos Thrampoulidis

Label-Imbalanced and Group-Sensitive Classification under Overparameterization


Shih-Yang Su · Frank Yu · Michael Zollhoefer · Helge Rhodin

A-NeRF: Articulated Neural Radiance Fields for Learning Human Shape, Appearance, and Pose


Weiwei Sun · Andrea Tagliasacchi · Boyang Deng · Sara Sabour · Soroosh Yazdani · Geoffrey Hinton · Kwang Moo Yi

Canonical Capsules: Self-Supervised Capsules in Canonical Pose


Ke Wang · Vidya Muthukumar · Christos Thrampoulidis

Benign Overfitting in Multiclass Classification: All Roads Lead to Interpolation


Ke ZHANG · Carl Yang · Xiaoxiao Li · Lichao Sun · Siu Ming Yiu

Subgraph Federated Learning with Missing Neighbor Generation




Note: All CAIDA Members have been bolded and a link has been provided to their personal webpages

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