raminmh / ordinary-neural-circuits
Code repo for paper: ICML 2020 paper Natural lottery ticket winner: RL for ordinary neural circuits
☆13Updated 4 years ago
Alternatives and similar repositories for ordinary-neural-circuits:
Users that are interested in ordinary-neural-circuits are comparing it to the libraries listed below
- Official repository for the paper "Neural Differential Equations for Learning to Program Neural Nets Through Continuous Learning Rules" (…☆21Updated 2 years ago
- An approach for embedding hierarhical structures into a continuous vector space using variational autoencoders.☆24Updated last year
- Neural Graphical models are neural network based graphical models that offer richer representation, faster inference & sampling☆28Updated last year
- A paper describing the implementation of PySR and SymbolicRegression.jl☆54Updated last year
- A python package for finding causal functional connectivity from neural time series observations.☆16Updated 2 months ago
- AI Physicist, a paradigm with algorithms for learning theories from data, by Wu and Tegmark (2019)☆34Updated 4 years ago
- Official code for paper: Conservative objective models are a special kind of contrastive divergence-based energy model☆14Updated last year
- Map-Elites based on Evolution Strategies☆31Updated 3 years ago
- ☆10Updated 4 years ago
- Causal discovery with typed directed acyclic graphs (t-DAG). This is a ServiceNow Research project that was started at Element AI.☆13Updated last year
- Example applications of path signatures☆38Updated 2 weeks ago
- NeuroMorphic Predictive Model with Spiking Neural Networks (SNN) using Pytorch☆29Updated 2 years ago
- Project for the financial forecasting challenge from G-Research (https://financialforecasting.gresearch.co.uk/).☆7Updated 7 years ago
- We propose an evolution-based approach to meta-learn synthetic neural environments and reward neural networks for reinforcement learning.☆21Updated 2 years ago
- Utilities for probabilistic ML☆33Updated last year
- Dynamic causal Bayesian optimisation☆35Updated last year
- Symbolic regression is the task of identifying a mathematical expression that best fits a provided dataset of input and output values. In…☆44Updated 3 years ago
- A barely barebone NumPy implementation of Hierarchical Temporal Memory.☆11Updated 2 years ago
- Official repository for the paper "Goal-Conditioned Generators of Deep Policies"☆11Updated 2 years ago
- Reverse engineering neural networks☆23Updated 2 weeks ago
- JAX-LOB: A GPU-Accelerated limit order book simulator to unlock large scale reinforcement learning for trading☆24Updated last year
- Uses several statistical tests / algorithms on marginal / conditional distributions☆8Updated last year
- ☆10Updated 2 years ago
- A basic implementation of the paper Eigengame : PCA as a Nash Equilibrium☆21Updated 3 years ago
- Numerically Solving Parametric Families of High-Dimensional Kolmogorov Partial Differential Equations via Deep Learning (NeurIPS 2020)☆22Updated 2 years ago
- Automatic Integration for Neural Spatio-Temporal Point Process models (AI-STPP) is a new paradigm for exact, efficient, non-parametric inf…☆24Updated 5 months ago
- Simulation code and detailed exposition of the free energy princple (FEP).☆9Updated 2 years ago
- Official repository for the paper "Automating Continual Learning"☆13Updated last year
- ☆31Updated 2 years ago
- Parallel random matrix tools and complexity for deep learning☆33Updated last year