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【论文阅读笔记】NeurIPS2020文章列表Part2_differentiable causal discovery from interventiona
作者:很楠不爱3 | 2024-04-07 01:15:01
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differentiable causal discovery from interventional data
Online Multitask Learning with Long-Term Memory
Fewer is More: A Deep Graph Metric Learning Perspective Using Fewer Proxies
Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting
On Reward-Free Reinforcement Learning with Linear Function Approximation
Robustness of Community Detection to Random Geometric Perturbations
Learning outside the Black-Box: The pursuit of interpretable models
Breaking Reversibility Accelerates Langevin Dynamics for Non-Convex Optimization
Robust large-margin learning in hyperbolic space
Replica-Exchange Nos’e-Hoover Dynamics for Bayesian Learning on Large Datasets
Adversarially Robust Few-Shot Learning: A Meta-Learning Approach
Neural Anisotropy Directions
Digraph Inception Convolutional Networks
PAC-Bayesian Bound for the Conditional Value at Risk
Stochastic Stein Discrepancies
On the Role of Sparsity and DAG Constraints for Learning Linear DAGs
Cream of the Crop: Distilling Prioritized Paths For One-Shot Neural Architecture Search
Fair Multiple Decision Making Through Soft Interventions
Representation Learning for Integrating Multi-domain Outcomes to Optimize Individualized Treatment
Learning to Play No-Press Diplomacy with Best Response Policy Iteration
Inverse Learning of Symmetries
DiffGCN: Graph Convolutional Networks via Differential Operators and Algebraic Multigrid Pooling
Distributed Newton Can Communicate Less and Resist Byzantine Workers
Efficient Nonmyopic Bayesian Optimization via One-Shot Multi-Step Trees
Effective Diversity in Population Based Reinforcement Learning
Elastic-InfoGAN: Unsupervised Disentangled Representation Learning in Class-Imbalanced Data
Direct Policy Gradients: Direct Optimization of Policies in Discrete Action Spaces
Hybrid Models for Learning to Branch
WoodFisher: Efficient Second-Order Approximation for Neural Network Compression
Bi-level Score Matching for Learning Energy-based Latent Variable Models
Counterfactual Contrastive Learning for Weakly-Supervised Vision-Language Grounding
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Worst-Case Analysis for Randomly Collected Data
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Reinforcement Learning in Factored MDPs: Oracle-Efficient Algorithms and Tighter Regret Bounds for the Non-Episodic Setting
Improving model calibration with accuracy versus uncertainty optimization
The Convolution Exponential and Generalized Sylvester Flows
An Improved Analysis of Stochastic Gradient Descent with Momentum
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GCN meets GPU: Decoupling “When to Sample” from “How to Sample”
Continual Learning of a Mixed Sequence of Similar and Dissimilar Tasks
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DisCor: Corrective Feedback in Reinforcement Learning via Distribution Correction
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Can I Trust My Fairness Metric? Assessing Fairness with Unlabeled Data and Bayesian Inference
RandAugment: Practical Automated Data Augmentation with a Reduced Search Space
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Variational Inference for Graph Convolutional Networks in the Absence of Graph Data and Adversarial Settings
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Learning Optimal Representations with the Decodable Information Bottleneck
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Improved Variational Bayesian Phylogenetic Inference with Normalizing Flows
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