[NeurIPS 2023] Training Energy-Based Normalizing Flow with Score-Matching Objectives
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Updated
Jun 19, 2024 - Python
[NeurIPS 2023] Training Energy-Based Normalizing Flow with Score-Matching Objectives
A practical method for training energy-based language models.
Version 2.0 of the Energy Economical Model improves upon the original EEM release (see separate repo) by adding support for bulk upload of load profile and existing source utilization as well as Battery Energy Storage Systems.
Energy Economical Model has been developed to quantitatively answer the following question for industrial units, "What is the best energy source mix for my facility and operations?"
The official repository of "Energy-Based Cross Attention for Bayesian Context Update in Text-to-Image Diffusion Models".
[CVPR 2024] TEA: Test-time Energy Adaptation
This repository contains the official code for Energy Transformer---an efficient Energy-based Transformer variant for graph classification
Naive implementations of deep reinforcement learning algorithms
The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation net…
Official PyTorch code for UAI 2023 paper "Concurrent Misclassification and Out-of-Distribution Detection for Semantic Segmentation via Energy-Based Normalizing Flow"
[AAAI 2022] Official Implementation of Active Learning for Domain Adaptation: An Energy-based Approach https://arxiv.org/abs/2112.01406
Noise Contrastive Estimation (NCE) in PyTorch
[NeurIPS 2023] Learning Energy-Based Prior Model with Diffusion-Amortized MCMC
[ICCV 2023] Unsupervised Compositional Concepts Discovery with Text-to-Image Generative Models
[NeurIPS 2022] (Amortized) distributional control for pre-trained generative models
Energy Based Models in PyTorch
Official code for the paper "Arbitrary Conditional Distributions with Energy".
[NeurIPS 2021 Spotlight] Learning to Compose Visual Relations
PyTorch implementation of JEM++: Improved Techniques for Training JEM
Extreme Q-Learning: Max Entropy RL without Entropy
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