LucasBoTang / GradNorm
PyTorch implementation of the GradNorm
☆61Updated 2 weeks ago
Related projects: ⓘ
- The Implementation of "Auto-Lambda: Disentangling Dynamic Task Relationships" [TMLR 2022].☆128Updated last year
- Official implementation of "Multi-Task Learning as a Bargaining Game" [ICML 2022]☆202Updated 4 months ago
- Pytorch implementation of the GradNorm. GradNorm addresses the problem of balancing multiple losses for multi-task learning by learning a…☆244Updated 2 years ago
- ☆57Updated 2 weeks ago
- AM207 project: dissect aleatoric and epistemic uncertainty☆79Updated 4 years ago
- Implementation of Deep evidential regression paper☆47Updated 3 years ago
- Official PyTorch Implementation for Conflict-Averse Gradient Descent (CAGrad)☆108Updated 10 months ago
- Paper List for Multi-Task Learning (focus on architectures and optimization for MTL)☆35Updated 9 months ago
- AdaTask: A Task-Aware Adaptive Learning Rate Approach to Multi-Task Learning. AAAI, 2023.☆22Updated 11 months ago
- ☆93Updated 3 years ago
- An implementation of the state-of-the-art Deep Active Learning algorithms☆97Updated last year
- Official repository for CVPR21 paper "Deep Stable Learning for Out-Of-Distribution Generalization".☆183Updated 2 years ago
- Evidential Deep Learning in PyTorch☆39Updated last year
- [ICML 2020] Efficient Continuous Pareto Exploration in Multi-Task Learning☆135Updated 3 years ago
- A pytorch implementation of MCDO(Monte-Carlo Dropout methods)☆55Updated 5 years ago
- Pytorch reimplementation for "Gradient Surgery for Multi-Task Learning"☆297Updated 3 years ago
- Official PyTorch Implementation for Fast Adaptive Multitask Optimization (FAMO)☆67Updated 4 months ago
- This in my Demo of Chen et al. "GradNorm: Gradient Normalization for Adaptive Loss Balancing in Deep Multitask Networks" ICML 2018☆165Updated 2 years ago
- Pytorch implementation of "What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?"☆155Updated 5 years ago
- Reproduction of the paper: Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles☆25Updated 4 years ago
- Code for MC Dropout and Model Ensembling Uncertainty Estimate experiments☆55Updated 4 years ago
- ☆71Updated last year
- ShellingFord221 / My-implementation-of-What-Uncertainties-Do-We-Need-in-Bayesian-Deep-Learning-for-Computer-VisionPytorch implementation of classification task in What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision (simple vers…☆74Updated 3 years ago
- AdaShare: Learning What To Share For Efficient Deep Multi-Task Learning☆110Updated 3 years ago
- ☆225Updated 4 years ago
- PyTorch Implementation of the Multi-gate Mixture-of-Experts with Exclusivity (MMoEEx)☆30Updated 3 years ago
- Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"☆267Updated 2 years ago
- Code for "Gradient Surgery for Multi-Task Learning"☆299Updated 4 years ago
- Code for Neural Information Processing Systems (NeurIPS) 2019 paper: Pareto Multi-Task Learning☆125Updated 4 years ago
- This repository is the code for Predictive Uncertainty Estimation using Deep Ensemble☆147Updated 2 years ago