Learn about the Neumorphic engineering process of creating large-scale integration (VLSI) systems containing electronic analog circuits to mimic neuro-biological architectures.

Pytorch implementation of Neural Processes for functions and images :fireworks:

Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.

Tensorflow implementation of Neural Scene Representation and Rendering

implementing "recurrent attentive neural processes" to forecast power usage (w. LSTM baseline, MCDropout)

A framework for composing Neural Processes in Python

PyTorch implementation of Neural Processes

A framework for composing Neural Processes in Julia

A Pytorch Implementation of Attentive Neural Process

Implementation of GQN in PyTorch

Official code implementation for SIGIR 23 paper Normalizing Flow-based Neural Process for Few-Shot Knowledge Graph Completion

[WWW 2021]Task-adaptive Neural Process for User Cold-Start Recommendation

Code for deep learning-based glioma/tumor growth models

Amortized Probabilistic Conditioning for Optimization, Simulation and Inference (Chang et al., AISTATS 2025)

This repository contains PyTorch implementations of Neural Process, Attentive Neural Process, and Recurrent Attentive Neural Process.

Probabilistic deep learning using JAX

Neural Time Series Analysis

Official repo to paper

No description provided.

Implementation of Contrastive Neural Processes in PyTorch

[ICLR'22] Multi-Task Neural Processes

ALINE: Joint Amortization for Bayesian Inference and Active Data Acquisition (Huang et al., NeurIPS 2025)

Quick experiment to see how neural processes do vs kriging, at gridding soil samples

Code for "GP-ConvCNP: Better Generalization for Convolutional Conditional Neural Processes on Time Series Data"

Neural Process implementations in JAX and PyTorch

Official implementation of Renyi Neural Processes (ICML 2025)

Keras, Tensorflow eager execution implementation of Neural Processes

Amortized Bayesian Experimental Design for Decision-Making (Huang et al., NeurIPS 2024)

Code to reproduce the results presented in the Informed Meta-Learning paper

LaTeX source for my PhD thesis Convolutional Conditional Neural Processes