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

Tensorflow implementation of Neural Scene Representation and Rendering

A framework for composing Neural Processes in Python

PyTorch implementation of Neural Processes

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

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

Probabilistic deep learning using JAX

Official repo to paper

Implementation of Contrastive Neural Processes in PyTorch

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

[ICLR'22] Multi-Task Neural Processes

Official implementation of Renyi Neural Processes (ICML 2025)

Keras, Tensorflow eager execution implementation of Neural Processes

This is a reproduction of Garnelo et al., Neural Processes. arXiv:1807.01622 [cs, stat] (2018).

Practical Equivariances via Relational Conditional Neural Processes (Huang et al., NeurIPS 2023)

Replication of the "Conditional Neural Processes" (2018) and "Neural Processes" (2018) papers by Garnelo et al.