cambridge-mlg / convcnp
Implementation of the Convolutional Conditional Neural Process
☆121Updated 3 years ago
Related projects ⓘ
Alternatives and complementary repositories for convcnp
- Pytorch implementation of Neural Processes for functions and images☆224Updated 2 years ago
- A Pytorch Implementation of Attentive Neural Process☆73Updated 5 years ago
- Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.☆202Updated 4 months ago
- A framework for composing Neural Processes in Python☆78Updated 4 months ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 4 years ago
- Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021☆23Updated last year
- Official code for the ICLR 2021 paper Neural ODE Processes☆71Updated 2 years ago
- ☆177Updated 5 years ago
- Experiments for the Neural Autoregressive Flows paper☆123Updated 3 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆86Updated 4 years ago
- Code for Neural Spline Flows paper☆259Updated 4 years ago
- A PyTorch Implementation of Convolutional Conditional Neural Process.☆48Updated 4 years ago
- Regularized Neural ODEs (RNODE)☆81Updated 3 years ago
- ODE2VAE: Deep generative second order ODEs with Bayesian neural networks☆123Updated 2 months ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆80Updated 4 years ago
- Implementation of the Functional Neural Process models☆43Updated 4 years ago
- Pytorch implementation of Block Neural Autoregressive Flow☆175Updated 3 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- Riemannian Convex Potential Maps☆68Updated last year
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆86Updated 2 years ago
- [IJCAI'19, NeurIPS'19] Anode: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs☆104Updated 4 years ago
- Official PyTorch BIVA implementation (BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling)☆82Updated last year
- Implementation and tutorials of normalizing flows with the novel distributions module☆160Updated 4 years ago
- Discrete Normalizing Flows implemented in PyTorch☆107Updated 3 years ago
- implementing "recurrent attentive neural processes" to forecast power usage (w. LSTM baseline, MCDropout)☆90Updated 8 months ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- ☆146Updated 2 years ago
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆72Updated last year
- Implementation of Unconstrained Monotonic Neural Network and the related experiments. These architectures are particularly useful for mod…☆116Updated 10 months ago
- Neural Spline Flow, RealNVP, Autoregressive Flow, 1x1Conv in PyTorch.☆270Updated 10 months ago