This year marks the 36th 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 intelligence and machine learning and promotes the exchange of research advances. The conference will take place from November 28th through December 9th and will be a Hybrid Conference with a physical component at the New Orleans Convention Center during the first week, and a virtual component the second week. This year fourteen of CAIDA's members have been featured with a total of 20 papers accepted. You can see a list of our members’ papers below, and you can find out more about this year’s conference here.
Bowen Baker · Ilge Akkaya · Peter Zhokov · Joost Huizinga · Jie Tang · Adrien Ecoffet · Brandon Houghton · Raul Sampedro · Jeff Clune
Video PreTraining (VPT): Learning to Act by Watching Unlabeled Online Videos
Naitong Chen · Zuheng Xu · Trevor Campbell
Bayesian inference via sparse Hamiltonian flows
Setareh Cohan · Nam Hee Kim · David Rolnick · Michiel van de Panne
Understanding the Evolution of Linear Regions in Deep Reinforcement Learning
William Harvey · Saeid Naderiparizi · Vaden Masrani · Christian Weilbach · Frank Wood
Flexible Diffusion Modeling of Long Videos
Xingzhe He · Bastian Wandt · Helge Rhodin
AutoLink: Self-supervised Learning of Human Skeletons and Object Outlines by Linking Keypoints
Yuhe Jin · Weiwei Sun · Jan Hosang · Eduard Trulls · Kwang Moo Yi
TUSK: Task-Agnostic Unsupervised Keypoints
Siddhesh Khandelwal · Leonid Sigal
Iterative Scene Graph Generation
Jiachang Liu · Chudi Zhong · Boxuan Li · Margo Seltzer · Cynthia Rudin
FasterRisk: Fast and Accurate Interpretable Risk Scores
Mohamad Amin Mohamadi · Wonho Bae · Danica J. Sutherland
Making Look-Ahead Active Learning Strategies Feasible with Neural Tangent Kernels
Cian Naik · Judith Rousseau · Trevor Campbell
Fast Bayesian Coresets via Subsampling and Quasi-Newton Refinement
DOU QI · Konstantinos Kamnitsas · Yuankai Huo · Xiaoxiao Li · Daniel Moyer · Danielle Pace · Jonas Teuwen · Islem Rekik
Medical Imaging meets NeurIPS
Rindra Ramamonjison · Amin Banitalebi-Dehkordi · Giuseppe Carenini · Bissan Ghaddar · Timothy Yu · Zirui Zhou · Yong Zhang
NL4Opt: Formulating Optimization Problems Based on Their Natural Language Descriptions
Ali Seyfi · Jean-Francois Rajotte · Raymond Ng
Group GAN
Hamed Shirzad · Kaveh Hassani · Danica J. Sutherland
Evaluating Graph Generative Models with Contrastively Learned Features
Haoyuan Sun · Kwangjun Ahn · Christos Thrampoulidis · Navid Azizan
Mirror Descent Maximizes Generalized Margin and Can Be Implemented Efficiently
Nikola Surjanovic · Saifuddin Syed · Alexandre Bouchard-Côté · Trevor Campbell
Parallel Tempering With a Variational Reference
Christos Thrampoulidis · Ganesh Ramachandra Kini · Vala Vakilian · Tina Behnia
Imbalance Trouble: Revisiting Neural-Collapse Geometry
Rui Xin · Chudi Zhong · Zhi Chen · Takuya Takagi · Margo Seltzer · Cynthia Rudin
Exploring the Whole Rashomon Set of Sparse Decision Trees
Jinsoo Yoo · Frank Wood
BayesPCN: A Continually Learnable Predictive Coding Associative Memory
Lijia Zhou · Frederic Koehler · Pragya Sur · Danica J. Sutherland · Nati Srebro
A Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized Linear Models
Note: All CAIDA Members have been bolded and a link has been provided to their personal webpages