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NeurIPS 2023 Accepted Papers

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Photo credit: https://nips.cc/

October 17, 2023

This year marks the 37th 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 December 10th through December 16th and will be a Hybrid Conference with a physical component at the New Orleans Ernest N. Morial Convention Center. 

This year thirteen of CAIDA's members have been featured with a total of 15 papers accepted.  You can see a list of our members’ papers below, and you can find out more about this year’s conference here.
 

Ali Behrouz, Farnoosh Hashemi, Sadaf Sadeghian, Margo Seltzer

CAT-Walk: Inductive Hypergraph Learning via Set Walks

 

Gaurav Bhatt, Deepayan Das, Leonid Sigal, Vineeth N Balasubramanian

Mitigating the Effect of Incidental Correlations on Part-based Learning

 

Alexandre Capone, Sandra Hirche, Geoff Pleiss

Sharp Calibrated Gaussian Processes

 

Chen Fan, Gaspard Choné-Ducasse, Mark Schmidt, Christos Thrampoulidis

BiSLS/SPS: Auto-tune Step Sizes for Stable Bi-level Optimization

 

Zhi Chen, Chudi Zhong, Margo Seltzer, Cynthia Rudin

Exploring and Interacting with the Set of Good Sparse Generalized Additive Models

 

Leonardo Galli, Holger Rauhut, Mark Schmidt

Don't be so Monotone: Relaxing Stochastic Line Search in Over-Parameterized Models

 

Devon Graham, Kevin Leyton-Brown, Tim Roughgarden

Utilitarian Algorithm Configuration

 

Eric Hedlin, Gopal Sharma, Shweta Mahajan, Hossam Isack, Abhishek Kar, Andrea Tagliasacchi, Kwang Moo Yi

Unsupervised Semantic Correspondence Using Stable Diffusion

 

Shengran Hu, Jeff Clune

Thought Cloning: Learning to Think while Acting by Imitating Human Thinking

 

Frederik Kunstner, Victor Sanches Portella, Mark Schmidt, Nicholas Harvey

Searching for Optimal Per-Coordinate Step-sizes with Multidimensional Backtracking

 

Chen Liang, Jiahui Yu, Ming-Hsuan Yang, Matthew Brown, Yin Cui, Tuo Zhao, Boqing Gong, Tianyi Zhou

Module-wise Adaptive Distillation for Multimodality Foundation Models

 

Matthew Niedoba, Jonathan Lavington, Yunpeng Liu, Vasileios Lioutas, Justice Sefas, Xiaoxuan Liang, Dylan Green, Setareh Dabiri, Berend Zwartsenberg, Adam Scibior, Frank Wood

A Diffusion-Model of Joint Interactive Navigation

 

Andres Potapczynski, Marc Finzi, Geoff Pleiss, Andrew Wilson

Exploiting Compositional Structure for Automatic and Efficient Numerical Linear Algebra

 

Yi Ren, Samuel Lavoie, Michael Galkin, Danica J. Sutherland, Aaron Courville

Improving Systematic Generalization using Iterated Learning and Simplicial Embeddings

 

Zuheng Xu, Trevor Campbell

Embracing the chaos: analysis and diagnosis of numerical instability in variational flows

 

 

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


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