Alternatives and similar repositories for recur

Users that are interested in recur are comparing it to the libraries listed below

• ermongroup / SPN_Variational_Inference
  PyTorch implementation for "Probabilistic Circuits for Variational Inference in Discrete Graphical Models", NeurIPS 2020
  ☆17Updated 4 years ago
• facebookresearch / symbolicregression
  SR based on LLMs.
  ☆116Updated 2 years ago
• omron-sinicx / srsd-benchmark
  [DMLR] Rethinking Symbolic Regression Datasets and Benchmarks for Scientific Discovery
  ☆37Updated last year
• deep-symbolic-mathematics / Multimodal-Math-Pretraining
  [ICLR 2024 Spotlight] This is the official code for the paper "SNIP: Bridging Mathematical Symbolic and Numeric Realms with Unified Pre-t…
  ☆58Updated last year
• HEmile / a-nesi
  A Scalable Approximate Method for Probabilistic Neurosymbolic Inference
  ☆16Updated 9 months ago
• priyankjaini / discFlowMH
  Pytorch code for Sampling in Combinatorial Spaces with SurVAE Flow Augmented MCMC
  ☆11Updated 4 years ago
• IDSIA / neuraldiffeq-fwp
  Official repository for the paper "Neural Differential Equations for Learning to Program Neural Nets Through Continuous Learning Rules" (…
  ☆23Updated 4 months ago
• EdinburghNLP / torch-adaptive-imle
  ☆34Updated 10 months ago
• mojivalipour / symbolicgpt
  Symbolic regression is the task of identifying a mathematical expression that best fits a provided dataset of input and output values. In…
  ☆53Updated 3 years ago
• dylandoblar / noether-networks
  Meta-learning inductive biases in the form of useful conserved quantities.
  ☆37Updated 2 years ago
• jambo6 / neuralRDEs
  Code for: "Neural Rough Differential Equations for Long Time Series", (ICML 2021)
  ☆118Updated 4 years ago
• LaurenceA / bayesfunc
  ☆15Updated 3 years ago
• tristandeleu / jax-dag-gflownet
  Code for "Bayesian Structure Learning with Generative Flow Networks"
  ☆92Updated 3 years ago
• neildhir / DCBO
  Dynamic causal Bayesian optimisation
  ☆40Updated 2 years ago
• pilancilab / scnn
  Scalable Convex Neural Networks
  ☆24Updated 6 months ago
• vvvm23 / mamba-jax
  Unofficial but Efficient Implementation of "Mamba: Linear-Time Sequence Modeling with Selective State Spaces" in JAX
  ☆88Updated last year
• ml-jku / quam
  Quantification of Uncertainty with Adversarial Models
  ☆29Updated 2 years ago
• joneswack / dp-rfs
  This repository contains PyTorch implementations of various random feature maps for dot product kernels.
  ☆22Updated last year
• google-deepmind / neural_testbed
  ☆192Updated 4 months ago
• pylon-lib / pylon
  ☆122Updated last year
• neuroevobench / neuroevobench
  Neuroevolution Benchmark in JAX 🦕
  ☆40Updated last year
• bhoov / energy-transformer-jax
  The Energy Transformer block, in JAX
  ☆58Updated last year
• gwgundersen / rflvm
  Random feature latent variable models in Python
  ☆23Updated 2 years ago
• jamesvuc / jax-bayes
  Bayesian inference with Python and Jax.
  ☆34Updated 2 years ago
• google-deepmind / PGMax
  Loopy belief propagation for factor graphs on discrete variables in JAX
  ☆157Updated last year
• KurochkinAlexey / AntisymmetricRNN
  Python implementation of paper "AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks"
  ☆15Updated 6 years ago
• teddykoker / grokking
  PyTorch implementation of "Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets"
  ☆37Updated 3 years ago
• deep-symbolic-mathematics / TPSR
  [NeurIPS 2023] This is the official code for the paper "TPSR: Transformer-based Planning for Symbolic Regression"
  ☆78Updated 11 months ago
• google-research / hyperbo
  Pre-trained Gaussian processes for Bayesian optimization
  ☆97Updated 6 months ago
• juliusberner / deep_kolmogorov
  Numerically Solving Parametric Families of High-Dimensional Kolmogorov Partial Differential Equations via Deep Learning (NeurIPS 2020)
  ☆22Updated 3 years ago