Code for NeurIPS 2023 Paper (Imitation Learning from Imperfection: Theoretical Justifications and Algorithms)
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Updated
Sep 22, 2023 - Python
Code for NeurIPS 2023 Paper (Imitation Learning from Imperfection: Theoretical Justifications and Algorithms)
Solution for NeurIPS 2023 - MedFM Challenge
Research code for NeurIPS 2023 paper "Modality-Independent Teachers Meet Weakly-Supervised Audio-Visual Event Parser"
[NeurIPS23] Locally differentially Private Decision Tree
Official implementation for "Tailoring Self-Attention for Graph via Rooted Subtrees" (NeurIPS2023)
Official implementation for "Tailoring Self-Attention for Graph via Rooted Subtrees" (NeurIPS2023)
[NeurIPS 2023] Learning Energy-Based Prior Model with Diffusion-Amortized MCMC
Curvature Filtrations for Graph Generative Model Evaluation
[NeurIPS 2023] Official code release accompanying the paper "NetHack is Hard to Hack" (Piterbarg, Pinto, Fergus)
[NeurIPS 2023] Counterfactual-Augmented Importance Sampling for Semi-Offline Policy Evaluation. https://arxiv.org/abs/2310.17146
[NeurIPS 2023 Spotlight] Code for "Contrastive Lift: 3D Object Instance Segmentation by Slow-Fast Contrastive Fusion"
[NeurIPS 2023 Spotlight] The Pursuit of Human Labeling: A New Perspective on Unsupervised Learning
Repo for our NeurIPS 2023 paper on: Divide, Evaluate, and Refine: Evaluating and Improving Text-to-Image Alignment with Iterative VQA Feedback
[NeurIPS 2023] Multi-fidelity hyperparameter optimization with deep power laws that achieves state-of-the-art results across diverse benchmarks.
The proceedings of top conference in 2023 on the topic of Reinforcement Learning (RL), including: AAAI, IJCAI, NeurIPS, ICML, ICLR, ICRA, AAMAS and more.
[NeurIPS 2023] PyTorch Implementation of "Social Motion Prediction with Cognitive Hierarchies"
Code for "Survival Permanental Processes for Survival Analysis with Time-Varying Covariates" at NeurIPS2023
[NeurIPS 2023] Act As You Wish: Fine-Grained Control of Motion Diffusion Model with Hierarchical Semantic Graphs
Official PyTorch Implementation for Advancing Bayesian Optimization via Learning Correlated Latent Space (CoBO)
[NeurIPS 2023 - ML for Audio Workshop (Oral)] Zero-shot audio captioning with audio-language model guidance and audio context keywords
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