Code for the ICML 2024 paper "Connecting the Dots: Is Mode-Connectedness the Key to Feasible Sample-Based Inference in Bayesian Neural Networks?"
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Updated
Jun 17, 2024 - Jupyter Notebook
Code for the ICML 2024 paper "Connecting the Dots: Is Mode-Connectedness the Key to Feasible Sample-Based Inference in Bayesian Neural Networks?"
Official code for "ZigZag: Universal Sampling-free Uncertainty Estimation Through Two-Step Inference" (TMLR 2024)
[ICML 2024] Code repository for "TIC-TAC: A Framework for Improved Covariance Estimation in Deep Heteroscedastic Regression". We address the problem of sub-optimal covariance estimation in deep heteroscedastic regression by proposing a new model and metric.
[ICML 2024] Let Go of Your Labels with Unsupervised Transfer
[ICML 2024] Outlier-Efficient Hopfield Layers for Large Transformer-Based Models
All graph/GNN papers accepted at the International Conference on Machine Learning (ICML) 2024.
Official PyTorch implementation of the ICML 2024 paper "Hyperbolic Active Learning for Semantic Segmentation under Domain Shift"
Compositional Capabilities of Autoregressive Transformers: A Study on Synthetic, Interpretable Tasks
[ICML 2024] Language Models Represent Beliefs of Self and Others
Official code for "Enabling Uncertainty Estimation in Iterative Neural Networks" (ICML 2024)
Official PyTorch implementation of "Stochastic Conditional Diffusion Models for Robust Semantic Image Synthesis" (ICML 2024).
Repository for "See More Details: Efficient Image Super-Resolution by Experts Mining", ICML 2024
The code repository for ICML24 paper "Tabular Insights, Visual Impacts: Transferring Expertise from Tables to Images"
Source code of the ICML24 paper "Self-Composing Policies for Scalable Continual Reinforcement Learning" (selected for oral presentation)
Repository of the paper "Exploring sequence landscape of biosynthetic gene clusters with protein language models" published at ICML2024 workshop Machine Learning for Life and Material Science: From Theory to Industry applications
Code and Data for the paper: Structure- and Function-Aware Substitution Matrices via Learnable Graph Matching (RECOMB 2024 & ICML 2024 Differentiable Almost Everything Workshop)
Official implementation for Zhong & Le et al., GNNs Also Deserve Editing, and They Need It More Than Once. ICML 2024
JAX reimplementation of the DeepMind paper "Genie: Generative Interactive Environments"
[ICML 2024] Author's Implementation of RVI-SAC
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