guilgautier / DPPy
Python toolbox for sampling Determinantal Point Processes
☆219Updated last month
Related projects: ⓘ
- ☆231Updated last year
- A PyTorch library for two-sample tests☆236Updated last year
- The collection of recent papers about variational inference☆84Updated 4 years ago
- Pytorch implementation of Hyperspherical Variational Auto-Encoders☆348Updated 4 years ago
- The collection of papers about combining deep learning and Bayesian nonparametrics☆117Updated 4 years ago
- Automated Scalable Bayesian Inference☆129Updated 2 years ago
- PyTorch re-implementation of parts of "Deep Sets" (NIPS 2017)☆68Updated 6 years ago
- Code for "A Meta Transfer Objective For Learning To Disentangle Causal Mechanisms"☆123Updated 5 years ago
- Code for "Stochastic Optimization of Sorting Networks using Continuous Relaxations", ICLR 2019.☆134Updated last year
- A Point Process Toolbox Based on PyTorch☆127Updated 4 years ago
- Hyperbolic Hierarchical Clustering.☆190Updated 11 months ago
- Understanding normalizing flows☆131Updated 4 years ago
- Source code for the paper "Hyperbolic Neural Networks", https://arxiv.org/abs/1805.09112☆171Updated 3 years ago
- Torch modules that wrap blackbox combinatorial solvers according to the method presented in "Differentiating Blackbox Combinatorial Solve…☆334Updated 2 years ago
- Repository containing Pytorch code for EKFAC and K-FAC perconditioners.☆139Updated last year
- ☆157Updated last month
- Reimplementation of Variational Inference with Normalizing Flows (https://arxiv.org/abs/1505.05770)☆224Updated 6 years ago
- Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning☆91Updated 3 years ago
- PyTorch code to run synthetic experiments.☆407Updated 3 years ago
- Neural Spline Flow, RealNVP, Autoregressive Flow, 1x1Conv in PyTorch.☆269Updated 9 months ago
- A community repository for benchmarking Bayesian methods☆108Updated 2 years ago
- Project site for "Your Classifier is Secretly an Energy-Based Model and You Should Treat it Like One"☆415Updated 2 years ago
- Contains code for the NeurIPS 2019 paper "Practical Deep Learning with Bayesian Principles"☆241Updated 4 years ago
- code for "Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders".☆123Updated 11 months ago
- PyTorch implementation of "Weight Uncertainty in Neural Networks"☆170Updated 2 years ago
- Efficient PyTorch Hessian eigendecomposition tools!☆355Updated 6 months ago
- Hypergradient descent☆137Updated 3 months ago
- Papers for Bayesian-NN☆314Updated 5 years ago
- Masked Autoregressive Flow☆198Updated last month
- Pytorch implementation of Neural Processes for functions and images☆223Updated 2 years ago