haebeom-lee / dropmaxLinks
Tensorflow implementation of DropMax: Adaptive Variational Softmax (NeurIPS2018)
☆18Updated 5 years ago
Alternatives and similar repositories for dropmax
Users that are interested in dropmax are comparing it to the libraries listed below
Sorting:
- Implementation of soft parameter sharing for neural networks☆69Updated 4 years ago
- Training Confidence-Calibrated Classifier for Detecting Out-of-Distribution Samples / ICLR 2018☆182Updated 5 years ago
- A DIRT-T Approach to Unsupervised Domain Adaptation (ICLR 2018)☆175Updated 7 years ago
- Pytorch Implementation of recent visual attribution methods for model interpretability☆146Updated 5 years ago
- Principled Detection of Out-of-Distribution Examples in Neural Networks☆202Updated 8 years ago
- Code for "Adversarial Distillation of Bayesian Neural Network Posteriors" https://arxiv.org/abs/1806.10317☆15Updated 6 years ago
- A PyTorch implementation of shake-shake☆111Updated 5 years ago
- This repo provides code used in the paper "Predicting with High Correlation Features" (https://arxiv.org/abs/1910.00164):☆54Updated 3 months ago
- Code for NeurIPS 2019 Paper, "L_DMI: An Information-theoretic Noise-robust Loss Function"☆119Updated 2 years ago
- Recent few-shot meta-learning papers☆86Updated 7 years ago
- [ICLR'19] Complement Objective Training☆76Updated 6 years ago
- Implements pytorch code for the Accelerated SGD algorithm.☆215Updated 7 years ago
- This project is the Torch implementation of our accepted AAAI 2018 paper : orthogonal weight normalization method for solving orthogonali…☆57Updated 5 years ago
- [ICLR'19] Meta-learning with differentiable closed-form solvers☆116Updated 5 years ago
- ☆32Updated 6 years ago
- Improving Consistency-Based Semi-Supervised Learning with Weight Averaging☆186Updated 6 years ago
- OD-test: A Less Biased Evaluation of Out-of-Distribution (Outlier) Detectors (PyTorch)☆62Updated last year
- Knowledge Transfer via Distillation of Activation Boundaries Formed by Hidden Neurons (AAAI 2019)☆105Updated 5 years ago
- Code repository for the VisDA-17 experiments in our paper 'Self-ensembling for Domain Adaptation'☆74Updated 3 years ago
- Robust loss functions for deep neural networks (CVPR 2017)☆91Updated 5 years ago
- Code for the paper "Generalizing to Unseen Domains via Adversarial Data Augmentation", NeurIPS 2018☆121Updated 5 years ago
- CVPR 2018 Hierarchical Novelty Detection for Visual Object Recognition☆39Updated 7 years ago
- PyTorch Implementations of Dropout Variants☆87Updated 7 years ago
- TRAINING DEEP NEURAL-NETWORKS USING A NOISE ADAPTATION LAYER☆118Updated 8 years ago
- Structured Bayesian Pruning, NIPS 2017☆74Updated 5 years ago
- Code for "EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis" https://arxiv.org/abs/1905.05934☆113Updated 5 years ago
- Gold Loss Correction☆87Updated 6 years ago
- Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch☆49Updated 7 years ago
- pytorch maml with Multi-GPUs, fast and simplest implementation☆13Updated 4 years ago
- ☆351Updated 5 years ago