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This program in Python allows the Kalman-TD Model to fit simulated behavioural data.
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
ND-Adam is a tailored version of Adam for training DNNs.
An open source python library for scalable Bayesian optimisation.
A pytorch library for graph and hypergraph computation.
PyTorch Implementation of the paper "Probabilistic Abduction for Visual Abstract Reasoning via Learning Rules in Vector-symbolic Architectures" published in the 3rd Workshop on Mathematical Reasoni…
PyTorch Implementation of the paper "A Neuro-vector-symbolic architecture for Solving Raven's Progressive Matrices" published in Nature Machine Intelligence 2023.
Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
The PSL software from the University of Maryland and the University of California Santa Cruz
Various examples to showcase the functionality of PSL.
Direct Feedback Alignment on MNIST dataset implemented in TF2.0/Keras API
「Direct Feedback Aligment를 이용한 신경망 학습 알고리즘 구현」에 대한 내용을 다루고 있습니다.
bioflax provides a JAX implementation of biologically plausible learning algorithms
Code for our paper on best practices to train neural networks with direct feedback alignment (DFA).
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphic…
An easy and fast way to create a Python GUI 🐍
A transactional, relational-graph-vector database that uses Datalog for query. The hippocampus for AI!
Sentence Classifications with Neural Networks
Entity Disambiguation as text extraction (ACL 2022)
REBEL is a seq2seq model that simplifies Relation Extraction (EMNLP 2021).
Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
machine learning with logical rules in Python
skope-rules: machine learning with logical rules in Python
Code for the MADDPG algorithm from the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"
