Papers
Exchangeable Neural ODE for Set Modeling
Yang Li, Haidong Yi, Christopher Bender et al.
Evaluating and Rewarding Teamwork Using Cooperative Game Abstractions
Tom Yan, Christian Kroer, Alexander Peysakhovich
Hierarchical Poset Decoding for Compositional Generalization in Language
Yinuo Guo, Zeqi Lin, Jian-Guang Lou et al.
Uncovering the Topology of Time-Varying fMRI Data using Cubical Persistence
Bastian Rieck, Tristan Yates, Christian Bock et al.
Sampling from a k-DPP without looking at all items
Daniele Calandriello, Michal Derezinski, Michal Valko
Bandit Samplers for Training Graph Neural Networks
Ziqi Liu, Zhengwei Wu, Zhiqiang Zhang et al.
On Uniform Convergence and Low-Norm Interpolation Learning
Lijia Zhou, Danica J. Sutherland, Nati Srebro
Barking up the right tree: an approach to search over molecule synthesis DAGs
John Bradshaw, Brooks Paige, Matt J Kusner et al.
Denoising Diffusion Probabilistic Models
Jonathan Ho, Ajay N. Jain, Pieter Abbeel
What Makes for Good Views for Contrastive Learning?
Yonglong Tian, Chen Sun, Ben Poole et al.
The Mean-Squared Error of Double Q-Learning
Wentao Weng, Harsh Gupta, Niao He et al.
Towards Interpretable Natural Language Understanding with Explanations as Latent Variables
Wangchunshu Zhou, Jinyi Hu, Hanlin Zhang et al.
Learning Strategic Network Emergence Games
Rakshit Trivedi, Hongyuan Zha
Online Structured Meta-learning
Huaxiu Yao, Yingbo Zhou, Mehrdad Mahdavi et al.
BlockGAN: Learning 3D Object-aware Scene Representations from Unlabelled Images
Thu H Nguyen-Phuoc, Christian Richardt, Long Mai et al.
Multipole Graph Neural Operator for Parametric Partial Differential Equations
Zongyi Li, Nikola Kovachki, Kamyar Azizzadenesheli et al.
Dynamic Regret of Policy Optimization in Non-Stationary Environments
Yingjie Fei, Zhuoran Yang, Zhaoran Wang et al.
Probabilistic Linear Solvers for Machine Learning
Jonathan Wenger, Philipp Hennig
On Correctness of Automatic Differentiation for Non-Differentiable Functions
Wonyeol Lee, Hangyeol Yu, Xavier Rival et al.
On Efficiency in Hierarchical Reinforcement Learning
Zheng Wen, Doina Precup, Morteza Ibrahimi et al.
Neural Controlled Differential Equations for Irregular Time Series
Patrick Kidger, James Morrill, James Foster et al.
Debiasing Distributed Second Order Optimization with Surrogate Sketching and Scaled Regularization
Michal Derezinski, Burak Bartan, Mert Pilanci et al.
Autoregressive Score Matching
Chenlin Meng, Lantao Yu, Yang Song et al.
Erdos Goes Neural: an Unsupervised Learning Framework for Combinatorial Optimization on Graphs
Nikolaos Karalias, Andreas Loukas