gnobitab / CertifiedMonotonicNetworkLinks
☆27Updated 2 years ago
Alternatives and similar repositories for CertifiedMonotonicNetwork
Users that are interested in CertifiedMonotonicNetwork are comparing it to the libraries listed below
Sorting:
- Implementation of Unconstrained Monotonic Neural Network and the related experiments. These architectures are particularly useful for mod…☆124Updated 9 months ago
- Code repo for "Function-Space Distributions over Kernels"☆32Updated 4 years ago
- ☆50Updated last year
- Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)☆53Updated 4 years ago
- CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training.☆78Updated last year
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated last year
- Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)☆42Updated 4 years ago
- General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.☆38Updated 3 years ago
- Pytorch version of "Deep Convolutional Networks as shallow Gaussian Processes" by Adrià Garriga-Alonso, Carl Rasmussen and Laurence Aitch…☆32Updated 5 years ago
- Material for the practical of the DS3 course on "Representing and comparing probabilities with kernels"☆26Updated 6 years ago
- Implementation of random Fourier features for kernel method, like support vector machine and Gaussian process model☆101Updated 11 months ago
- An encoder-decoder framework for learning from incomplete data☆45Updated 2 years ago
- Accompanying code for AAAI 2021 publication - High-Dimensional Bayesian Optimization via Tree-Structured Additive Models☆11Updated last year
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆39Updated 6 years ago
- A short course on temporal point process and modeling irregular time series☆21Updated 4 years ago
- BOAH: Bayesian Optimization & Analysis of Hyperparameters☆67Updated 5 years ago
- implementing "recurrent attentive neural processes" to forecast power usage (w. LSTM baseline, MCDropout)☆98Updated 6 months ago
- ☆17Updated 6 years ago
- A distributed version of the sparse multi-output Gaussian process framework integrating python and C++.☆30Updated 7 years ago
- Dirichlet Process K-means☆48Updated last year
- Official codebase for "Distribution-Free, Risk-Controlling Prediction Sets"☆85Updated last year
- Code for: "Neural Rough Differential Equations for Long Time Series", (ICML 2021)☆118Updated 4 years ago
- Code for Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding☆23Updated 2 years ago
- Deep Gaussian Processes with Doubly Stochastic Variational Inference☆151Updated 6 years ago
- Talks from Neil Lawrence☆54Updated last year
- Experiments for Neural Flows paper☆98Updated 3 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 4 years ago
- Repository for code release of paper "Robust Variational Autoencoders for Outlier Detection and Repair of Mixed-Type Data" (AISTATS 2020)☆50Updated 5 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆85Updated 5 years ago
- Bayesian neural network package☆151Updated 4 years ago