jramapuram / SimulatedAnnealing
Pytorch Optimizer for Simulated Annealing
☆23Updated 6 years ago
Related projects ⓘ
Alternatives and complementary repositories for SimulatedAnnealing
- Bayesian Neural Network in PyTorch☆79Updated 6 months ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆80Updated 4 months ago
- Variational auto encoder in pytorch☆54Updated 5 years ago
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆72Updated last year
- Deep Neural Networks Entropy from Replicas☆32Updated 5 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- ☆66Updated 5 years ago
- Padé Activation Units: End-to-end Learning of Activation Functions in Deep Neural Network☆64Updated 3 years ago
- Source code for paper Choromanska et al. -- Beyond Backprop: Online Alternating Minimization with Auxiliary Variables -- http://proceedin…☆24Updated 5 years ago
- Stochastic Gradient Langevin Dynamics for Bayesian learning☆30Updated 2 years ago
- Bayesianize: A Bayesian neural network wrapper in pytorch☆86Updated 5 months ago
- Learning error bars for neural network predictions☆68Updated 4 years ago
- ☆61Updated 4 years ago
- Resources and Implementations (PyTorch) for Information Theoretical concepts in Deep Learning☆41Updated 5 years ago
- General API for Deep Bayesian Variational Inference by Backpropagation. The repository has been designed to work with Transformers like a…☆41Updated 4 years ago
- ☆70Updated 4 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 3 years ago
- ☆27Updated 5 years ago
- Code to accompany the paper Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning☆33Updated 4 years ago
- pyhessian is a TensorFlow module which can be used to estimate Hessian matrices☆23Updated 3 years ago
- Code for paper: SDE-Net: Equipping Deep Neural network with Uncertainty Estimates☆109Updated 4 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 4 years ago
- Hypergradient descent☆138Updated 5 months ago
- Several implementations of the kernel-based activation functions☆61Updated 5 years ago
- Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, …☆110Updated 5 years ago
- Experimenting with different regression losses. Implemented in Pytorch.☆144Updated 5 years ago
- Official code for UnICORNN (ICML 2021)☆27Updated 3 years ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 4 years ago
- Code base for SRSGD.☆28Updated 4 years ago
- Pytorch version of "Deep Convolutional Networks as shallow Gaussian Processes" by Adrià Garriga-Alonso, Carl Rasmussen and Laurence Aitch…☆32Updated 4 years ago