Pytorch implementation of Neural Processes for functions and images 🎆
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Updated
Feb 8, 2022 - Jupyter Notebook
Pytorch implementation of Neural Processes for functions and images 🎆
Learn about the Neumorphic engineering process of creating large-scale integration (VLSI) systems containing electronic analog circuits to mimic neuro-biological architectures.
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
A Pytorch Implementation of Attentive Neural Process
Implementation of GQN in PyTorch
[WWW 2021]Task-adaptive Neural Process for User Cold-Start Recommendation
Code for "GP-ConvCNP: Better Generalization for Convolutional Conditional Neural Processes on Time Series Data"
A framework for composing Neural Processes in Julia
Code for deep learning-based glioma/tumor growth models
Official repo to paper
Neural Time Series Analysis
This repository contains PyTorch implementations of Neural Process, Attentive Neural Process, and Recurrent Attentive Neural Process.
Official code implementation for SIGIR 23 paper Normalizing Flow-based Neural Process for Few-Shot Knowledge Graph Completion
[ICLR'22] Multi-Task Neural Processes
Neural Process implementations in JAX and PyTorch
Probabilistic deep learning using JAX
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