NeurIPS

The Edge-of-Reach Problem in Offline Model-Based Reinforcement Learning

Anya Sims, Cong Lu, Jakob Foerster, Yee Whye Teh

Comments Code open-sourced at: https://github.com/anyasims/edge-of-reach

Journal ref NeurIPS 2024

A framework for bilevel optimization that enables stochastic and global variance reduction algorithms

Mathieu Dagréou, Pierre Ablin, Samuel Vaiter, Thomas Moreau

Comments Accepted at NeurIPS 2022

AlphaTablets: A Generic Plane Representation for 3D Planar Reconstruction from Monocular Videos

Yuze He, Wang Zhao, Shaohui Liu, Yubin Hu, Yushi Bai, Yu-Hui Wen, Yong-Jin Liu

Comments NeurIPS 2024

Dual Risk Minimization: Towards Next-Level Robustness in Fine-tuning Zero-Shot Models

Kaican Li, Weiyan Xie, Yongxiang Huang, Didan Deng, Lanqing Hong, Zhenguo Li, Ricardo Silva, Nevin L. Zhang

Comments NeurIPS 2024

COLD: Causal reasOning in cLosed Daily activities

Abhinav Joshi, Areeb Ahmad, Ashutosh Modi

Comments Paper accepted at NeurIPS 2024; Total 37 Pages

An Adversarial Learning Approach to Irregular Time-Series Forecasting

Heejeong Nam, Jihyun Kim, Jimin Yeom

Comments Accepted to AdvML-Frontiers Workshop @ NeurIPS 2024

On the Ethical Considerations of Generative Agents

N'yoma Diamond, Soumya Banerjee

Comments Accepted (poster) to Socially Responsible Language Modelling Research (SoLaR) Workshop at NeurIPS 2024

Fast, Precise Thompson Sampling for Bayesian Optimization

David Sweet

Comments NeurIPS 2024 Workshop on Bayesian Decision-making and Uncertainty; Poster

Enhancing the Expressivity of Temporal Graph Networks through Source-Target Identification

Benedict Aaron Tjandra, Federico Barbero, Michael Bronstein

Comments Accepted to NeurIPS Symmetry and Geometry in Neural Representations Workshop 2024 (Oral)

Climate Adaptation with Reinforcement Learning: Experiments with Flooding and Transportation in Copenhagen

Miguel Costa, Morten W. Petersen, Arthur Vandervoort, Martin Drews, Karyn Morrissey, Francisco C. Pereira

Comments Accepted for presentation at Tackling Climate Change with Machine Learning workshop at NeurIPS 2024

Journal ref Tackling Climate Change with Machine Learning workshop at NeurIPS 2024

Recursive Nested Filtering for Efficient Amortized Bayesian Experimental Design

Sahel Iqbal, Hany Abdulsamad, Sara Pérez-Vieites, Simo Särkkä, Adrien Corenflos

Comments Accepted to NeurIPS BDU Workshop 2024

Open-Source Molecular Processing Pipeline for Generating Molecules

V Shreyas, Jose Siguenza, Karan Bania, Bharath Ramsundar

Comments Presented at the Molecular Machine Learning Conference 2024 (MoML 2024), BayLearn 2024 and the Machine Learning and Physical Sciences (ML4PS) Workshop at NeurIPS 2024

Evaluating language models as risk scores

André F. Cruz, Moritz Hardt, Celestine Mendler-Dünner

Journal ref NeurIPS 2024

Boosting Unsupervised Segmentation Learning

Alp Eren Sari, Francesco Locatello, Paolo Favaro

Comments Accepted to NeurIPS 2024 Workshop: Self-Supervised Learning - Theory and Practice

OneBit: Towards Extremely Low-bit Large Language Models

Yuzhuang Xu, Xu Han, Zonghan Yang, Shuo Wang, Qingfu Zhu, Zhiyuan Liu, Weidong Liu, Wanxiang Che

Comments Accepted by NeurIPS 2024

Do LLMs dream of elephants (when told not to)? Latent concept association and associative memory in transformers

Yibo Jiang, Goutham Rajendran, Pradeep Ravikumar, Bryon Aragam

Comments NeurIPS 2024

Paralinguistics-Aware Speech-Empowered Large Language Models for Natural Conversation

Heeseung Kim, Soonshin Seo, Kyeongseok Jeong, Ohsung Kwon, Soyoon Kim, Jungwhan Kim, Jaehong Lee, Eunwoo Song, Myungwoo Oh, Jung-Woo Ha, Sungroh Yoon, Kang Min Yoo

Comments NeurIPS 2024, Project Page: https://unifiedsdm.github.io/

ManiPose: Manifold-Constrained Multi-Hypothesis 3D Human Pose Estimation

Cédric Rommel, Victor Letzelter, Nermin Samet, Renaud Marlet, Matthieu Cord, Patrick Pérez, Eduardo Valle

Comments Accepted to NeurIPS 2024

Continuous Autoregressive Models with Noise Augmentation Avoid Error Accumulation

Marco Pasini, Javier Nistal, Stefan Lattner, George Fazekas

Comments Accepted to NeurIPS 2024 - Audio Imagination Workshop

Probabilistic size-and-shape functional mixed models

Fangyi Wang, Karthik Bharath, Oksana Chkrebtii, Sebastian Kurtek

Comments NeurIPS 2024

Prediction with Action: Visual Policy Learning via Joint Denoising Process

Yanjiang Guo, Yucheng Hu, Jianke Zhang, Yen-Jen Wang, Xiaoyu Chen, Chaochao Lu, Jianyu Chen

Comments NeurIPS 2024

Using different sources of ground truths and transfer learning to improve the generalization of photometric redshift estimation

Jonathan Soriano, Srinath Saikrishnan, Vikram Seenivasan, Bernie Boscoe, Jack Singal, Tuan Do

Comments 10 pages, 4 figures, 2 tables, accepted to NeurIPS 2024 Workshop ML4PS

Convolutional Vision Transformer for Cosmology Parameter Inference

Yash Gondhalekar, Kana Moriwaki

Comments Accepted at the NeurIPS ML4PS Workshop 2024. The code is available at https://github.com/Yash-10/cvt-cosmo-inference/

How Does Variance Shape the Regret in Contextual Bandits?

Zeyu Jia, Jian Qian, Alexander Rakhlin, Chen-Yu Wei

Comments NeurIPS 2024

Markov Equivalence and Consistency in Differentiable Structure Learning

Chang Deng, Kevin Bello, Pradeep Ravikumar, Bryon Aragam

Comments 38 pages, 14 figures, to appear at NeurIPS 2024

A Unified Framework for 3D Scene Understanding

Wei Xu, Chunsheng Shi, Sifan Tu, Xin Zhou, Dingkang Liang, Xiang Bai

Comments Accepted to NeurIPS 2024. Code and models are available at https://github.com/dk-liang/UniSeg3D

Bench2Drive: Towards Multi-Ability Benchmarking of Closed-Loop End-To-End Autonomous Driving

Xiaosong Jia, Zhenjie Yang, Qifeng Li, Zhiyuan Zhang, Junchi Yan

Comments Accepted by NeurIPS 2024 Datasets and Benchmarks Track. Official Repo: https://github.com/Thinklab-SJTU/Bench2Drive

CoMat: Aligning Text-to-Image Diffusion Model with Image-to-Text Concept Matching

Dongzhi Jiang, Guanglu Song, Xiaoshi Wu, Renrui Zhang, Dazhong Shen, Zhuofan Zong, Yu Liu, Hongsheng Li

Comments NeurIPS 2024

Activity Sparsity Complements Weight Sparsity for Efficient RNN Inference

Rishav Mukherji, Mark Schöne, Khaleelulla Khan Nazeer, Christian Mayr, Anand Subramoney

Comments Accepted to the First MLNCP Workshop @ NeurIPS 2023

From RNNs to Foundation Models: An Empirical Study on Commercial Building Energy Consumption

Shourya Bose, Yijiang Li, Amy Van Sant, Yu Zhang, Kibaek Kim

Comments NeurIPS 2024 Workshop on Time Series in the Age of Large Models