Papers
AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity
Silviu-Marian Udrescu, Andrew Tan, Jiahai Feng et al.
Hierarchically Organized Latent Modules for Exploratory Search in Morphogenetic Systems
Mayalen Etcheverry, Clément Moulin-Frier, Pierre-Yves Oudeyer
Deep Multimodal Fusion by Channel Exchanging
Yikai Wang, Wenbing Huang, Fuchun Sun et al.
Learning Implicit Functions for Topology-Varying Dense 3D Shape Correspondence
Feng Liu, Xiaoming Liu
Deep Variational Instance Segmentation
Jialin Yuan, Chao Chen, Fuxin Li
Improved Algorithms for Convex-Concave Minimax Optimization
Yuanhao Wang, Jian Li
On the training dynamics of deep networks with L_2 regularization
Aitor Lewkowycz, Guy Gur-Ari
Causal Shapley Values: Exploiting Causal Knowledge to Explain Individual Predictions of Complex Models
Tom Heskes, Evi Sijben, Ioan Gabriel Bucur et al.
Multi-Task Reinforcement Learning with Soft Modularization
Ruihan Yang, Huazhe Xu, YI WU et al.
Towards More Practical Adversarial Attacks on Graph Neural Networks
Jiaqi Ma, Shuangrui Ding, Qiaozhu Mei
Generative View Synthesis: From Single-view Semantics to Novel-view Images
Tewodros Amberbir Habtegebrial, Varun Jampani, Orazio Gallo et al.
Learning Representations from Audio-Visual Spatial Alignment
Pedro Morgado, Yi Li, Nuno Nvasconcelos
Randomized tests for high-dimensional regression: A more efficient and powerful solution
Yue Li, Ilmun Kim, Yuting Wei
Unsupervised Learning of Object Landmarks via Self-Training Correspondence
Dimitrios Mallis, Enrique Sanchez, Matthew Bell et al.
Bayesian Deep Learning and a Probabilistic Perspective of Generalization
Andrew G Wilson, Pavel Izmailov
Robust Meta-learning for Mixed Linear Regression with Small Batches
Weihao Kong, Raghav Somani, Sham Kakade et al.
A Non-Asymptotic Analysis for Stein Variational Gradient Descent
Anna Korba, Adil Salim, Michael Arbel et al.
Labelling unlabelled videos from scratch with multi-modal self-supervision
Yuki Asano, Mandela Patrick, Christian Rupprecht et al.
Your Classifier can Secretly Suffice Multi-Source Domain Adaptation
Naveen Venkat, Jogendra Nath Kundu, Durgesh Singh et al.
Probabilistic Circuits for Variational Inference in Discrete Graphical Models
Andy Shih, Stefano Ermon
Privacy Amplification via Random Check-Ins
Borja Balle, Peter Kairouz, Brendan McMahan et al.
Efficient Low Rank Gaussian Variational Inference for Neural Networks
Marcin Tomczak, Siddharth Swaroop, Richard Turner
Temporal Positive-unlabeled Learning for Biomedical Hypothesis Generation via Risk Estimation
Uchenna Akujuobi, Jun Chen, Mohamed Elhoseiny et al.
Reverse-engineering recurrent neural network solutions to a hierarchical inference task for mice
Rylan Schaeffer, Mikail Khona, Leenoy Meshulam et al.
Variational Policy Gradient Method for Reinforcement Learning with General Utilities
Junyu Zhang, Alec Koppel, Amrit Singh Bedi et al.