UBC Computer Science has 11 papers accepted at NeurIPS 2023 conference
12 professors from the Computer Science Department at the University of British Columbia (and their co-authors) have had 11 papers in total accepted for the 2023 NeurIPS conference
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 10 – 16 and will be a Hybrid Conference with a physical component at the Convention Center in New Orleans.
You can see a list of our members’ papers below. The UBC computer science professors for each paper below are in red and have a link to their personal website.
CAT-Walk: Inductive Hypergraph Learning via Set Walks
Ali Behrouz, Farnoosh Hashemi, Sadaf Sadeghian, Margo Seltzer
Mitigating the Effect of Incidental Correlations on Part-based Learning (poster)
Gaurav Bhatt, Deepayan Das, Leonid Sigal, Vineeth N Balasubramanian
BiSLS/SPS: Auto-tune Step Sizes for Stable Bi-level Optimization
Chen Fan, Gaspard Choné-Ducasse, Mark Schmidt, Christos Thrampoulidis
Exploring and Interacting with the Set of Good Sparse Generalized Additive Models
Zhi Chen, Chudi Zhong, Margo Seltzer, Cynthia Rudin
Don't be so Monotone: Relaxing Stochastic Line Search in Over-Parameterized Models
Leonardo Galli, Holger Rauhut, Mark Schmidt
Utilitarian Algorithm Configuration
Devon Graham, Kevin Leyton-Brown, Tim Roughgarden
Unsupervised Semantic Correspondence Using Stable Diffusion
Eric Hedlin, Gopal Sharma, Shweta Mahajan, Hossam Isack, Abhishek Kar, Andrea Tagliasacchi, Kwang Moo Yi
Thought Cloning: Learning to Think while Acting by Imitating Human Thinking
Shengran Hu, Jeff Clune
Searching for Optimal Per-Coordinate Step-sizes with Multidimensional Backtracking
Frederik Kunstner, Victor Sanches Portella, Mark Schmidt, Nicholas Harvey
A Diffusion-Model of Joint Interactive Navigation
Matthew Niedoba, Jonathan Lavington, Yunpeng Liu, Vasileios Lioutas, Justice Sefas, Xiaoxuan Liang, Dylan Green, Setareh Dabiri, Berend Zwartsenberg, Adam Scibior, Frank Wood
Improving Compositional Generalization using Iterated Learning and Simplicial Embeddings
Yi Ren, Samuel Lavoie, Michael Galkin, Danica J. Sutherland, Aaron Courville