tung-nd / TNP-pytorchLinks
Official implementation of Transformer Neural Processes
☆78Updated 3 years ago
Alternatives and similar repositories for TNP-pytorch
Users that are interested in TNP-pytorch are comparing it to the libraries listed below
Sorting:
- Neural Diffusion Processes☆81Updated last year
- Pytorch implementation of neural processes and variants☆29Updated last year
- Code for A General Recipe for Likelihood-free Bayesian Optimization, ICML 2022☆45Updated 3 years ago
- Featurized Density Ratio Estimation☆20Updated 4 years ago
- Official code for the ICLR 2021 paper Neural ODE Processes☆75Updated 3 years ago
- Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"☆44Updated 4 years ago
- ☆17Updated 3 years ago
- Code for our paper "Generative Flow Networks for Discrete Probabilistic Modeling"☆84Updated 2 years ago
- Official Release of "Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling"☆49Updated 5 years ago
- Package for working with hypernetworks in PyTorch.☆131Updated 2 years ago
- A PyTorch implementation of a Generative Flow Network (GFlowNet) proposed by Bengio et al. (2021)☆43Updated 2 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago
- Sampling with gradient-based Markov Chain Monte Carlo approaches☆108Updated last year
- Noise Contrastive Estimation (NCE) in PyTorch☆32Updated 7 months ago
- Code for reproducing results in the sliced score matching paper (UAI 2019)☆147Updated 5 years ago
- Code for our TMLR paper "Distributional GFlowNets with Quantile Flows".☆13Updated last year
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆77Updated 2 years ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 3 years ago
- Experiments for Neural Flows paper☆98Updated 3 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆89Updated 5 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)☆48Updated 4 years ago
- PyTorch implementation of the mixture distribution family with implicit reparametrisation gradients.☆19Updated last year
- [ICML'21] Improved Contrastive Divergence Training of Energy Based Models☆66Updated 3 years ago
- Experiments from the paper "On Second Order Behaviour in Augmented Neural ODEs"☆60Updated last year
- ☆53Updated 4 years ago
- A Pytorch Implementation of Attentive Neural Process☆75Updated 6 years ago
- Truncated Normal Distribution in PyTorch☆85Updated last year
- [NeurIPS'20] Code for the Paper Compositional Visual Generation and Inference with Energy Based Models☆46Updated 2 years ago
- NeurIPS'23: Energy Discrepancies: A Score-Independent Loss for Energy-Based Models☆17Updated last year