Alternatives and similar repositories for predict_tc

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

• sathya-chitturi / multibax-sklearn
  Design space subset estimation using Bayesian algorithm execution with sklearn GP models
  ☆25Updated last year
• google-research / e3x
  E3x is a JAX library for constructing efficient E(3)-equivariant deep learning architectures built on top of Flax.
  ☆109Updated 7 months ago
• blondegeek / e3nn_symm_breaking
  Code repository for "Finding symmetry breaking order parameters with Euclidean Neural Networks"
  ☆16Updated 4 years ago
• sail-sg / d4ft
  A JAX library for Density Functional Theory.
  ☆54Updated this week
• majhas / self-refining-dft
  ☆25Updated 4 months ago
• usccolumbia / Awesome-Machine-learning-for-discovery-of-physical-laws
  A curated list of awesome resources on using machine learning and data science for discovery of physical laws
  ☆36Updated 5 years ago
• gerkone / segnn-jax
  Steerable E(3) GNN in jax
  ☆24Updated 2 years ago
• lfoppiano / SuperMat
  Superconductors material dataset
  ☆26Updated last year
• google-deepmind / flows_for_atomic_solids
  ☆53Updated 3 years ago
• mdsunivie / deeperwin
  DeepErwin is a python 3.8+ package that implements and optimizes JAX 2.x wave function models for numerical solutions to the multi-electr…
  ☆63Updated 7 months ago
• n-gao / pesnet
  Reference implementation of "Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave Functions" (ICLR, 2022) and "Sampling-f…
  ☆31Updated last year
• Fung-Lab / StructRepGen
  Atomic Structure Generation from Reconstructing Structural Fingerprints
  ☆15Updated 3 years ago
• DavidRuhe / clifford-group-equivariant-neural-networks
  Code used by the "Clifford Group Equivariant Neural Networks" paper.
  ☆88Updated last year
• williamratcliff / GNN-tutorial-APS-March-2023
  These are the slides associated with the GNN tutorial at the APS March Meeting
  ☆21Updated 2 years ago
• gcucurull / jax-gcn
  Graph Convolutional Networks in JAX
  ☆33Updated 4 years ago
• jxzhangjhu / MatDesINNe
  Inverse materials design via invertible neural networks
  ☆65Updated 2 years ago
• ulissigroup / uncertainty_benchmarking
  Various code/notebooks to benchmark different ways we could estimate uncertainty in ML predictions.
  ☆42Updated 4 years ago
• scifm / summer-school-2024
  ☆39Updated last year
• vstanev1 / Supercon
  Data used in "Machine learning modeling of superconducting critical temperature" paper
  ☆31Updated 7 years ago
• IntelLabs / matsciml
  Open MatSci ML Toolkit is a framework for prototyping and scaling out deep learning models for materials discovery supporting widely used…
  ☆182Updated 8 months ago
• oconradh / benchmark_aflow
  Benchmark AFLOW Data Sets for Machine Learning doi.org/10.1007/s40192-020-00174-4
  ☆11Updated 5 years ago
• ur-whitelab / BO-ICL
  BayesOpt + LIFT
  ☆74Updated 6 months ago
• ziatdinovmax / SciLink
  Connecting experimental materials science with computational modeling and literature analysis via LLM-powered agents
  ☆39Updated this week
• CFN-softbio / SciBot
  SciBot is a simple demo of building a domain-specific chatbot for science.
  ☆31Updated last year
• CederGroupHub / sparse-lm
  Sparse Linear Regression Models
  ☆19Updated 2 weeks ago
• juliusberner / deep_kolmogorov
  Numerically Solving Parametric Families of High-Dimensional Kolmogorov Partial Differential Equations via Deep Learning (NeurIPS 2020)
  ☆22Updated 3 years ago
• mala-project / mala
  Materials Learning Algorithms. A framework for machine learning materials properties from first-principles data.
  ☆97Updated 2 months ago
• divelab / MFA
  Official code repository of paper Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency.
  ☆19Updated 10 months ago
• aspuru-guzik-group / Pasithea
  Deep Molecular Dreaming
  ☆25Updated last year
• lamalab-org / chembench-paper
  ☆25Updated 10 months ago