Alternatives and similar repositories for monotonic-nn

Users that are interested in monotonic-nn are comparing it to the libraries listed below

• tristandeleu / jax-dag-gflownet
  Code for "Bayesian Structure Learning with Generative Flow Networks"
  ☆87Updated 3 years ago
• niklasnolte / MonotonicNetworks
  ☆46Updated last year
• phlippe / ENCO
  Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"
  ☆83Updated last year
• bradyneal / realcause
  Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…
  ☆75Updated 4 years ago
• larslorch / avici
  Amortized Inference for Causal Structure Learning, NeurIPS 2022
  ☆64Updated 3 months ago
• fishmoon1234 / DAG-NoCurl
  ☆25Updated 3 years ago
• jmoss20 / notears
  Implementation of "DAGs with NO TEARS: Smooth Optimization for Structure Learning", by Zheng et al. (2018)
  ☆49Updated 6 years ago
• shchur / ifl-tpp
  Implementation of "Intensity-Free Learning of Temporal Point Processes" (Spotlight @ ICLR 2020)
  ☆85Updated 4 years ago
• seedatnabeel / TE-CDE
  Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations (ICML 2022)
  ☆27Updated 2 years ago
• kevinsbello / dagma
  A Python 3 package for learning Bayesian Networks (DAGs) from data. Official implementation of the paper "DAGMA: Learning DAGs via M-matr…
  ☆119Updated last year
• ignavierng / golem
  On the Role of Sparsity and DAG Constraints for Learning Linear DAGs
  ☆33Updated 3 years ago
• microsoft / csuite
  CSuite: A Suite of Benchmark Datasets for Causality
  ☆67Updated 2 years ago
• yangalan123 / anhp-andtt
  Codebase for Attentive Neural Hawkes Process (A-NHP) and Attentive Neural Datalog Through Time (A-NDTT)
  ☆58Updated 5 months ago
• Valentyn1997 / CausalTransformer
  Code for the paper "Causal Transformer for Estimating Counterfactual Outcomes"
  ☆149Updated 9 months ago
• BorealisAI / continuous-time-flow-process
  PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)
  ☆48Updated 4 years ago
• juangamella / ges
  Python implementation of the GES algorithm for causal discovery, from the 2002 paper "Optimal Structure Identification With Greedy Search…
  ☆59Updated 3 months ago
• yangalan123 / TemporalPointProcessPapers
  Paper lists for Temporal Point Process
  ☆110Updated 7 months ago
• AWehenkel / UMNN
  Implementation of Unconstrained Monotonic Neural Network and the related experiments. These architectures are particularly useful for mod…
  ☆118Updated 5 months ago
• chritoth / active-bayesian-causal-inference
  Active Bayesian Causal Inference (Neurips'22)
  ☆54Updated 10 months ago
• automl / PFNs
  Our maintained PFN repository. Come here to train SOTA PFNs.
  ☆87Updated this week
• py-why / dodiscover
  [Experimental] Global causal discovery algorithms
  ☆101Updated 3 months ago
• hlzhang109 / TransTEE
  ☆33Updated 2 years ago
• CausalAILab / NeuralCausalModels
  Neural Causal Model (NCM) implementation by the authors of The Causal Neural Connection.
  ☆24Updated 2 years ago
• ignavierng / notears-tensorflow
  Reimplementation of NOTEARS in Tensorflow
  ☆33Updated 2 years ago
• kurowasan / GraN-DAG
  ☆92Updated 2 years ago
• yandex-research / tabred
  (ICLR 2025 Spotlight) TabReD: Analyzing Pitfalls and Filling the Gaps in Tabular Deep Learning Benchmarks
  ☆72Updated last week
• psanch21 / causal-flows
  ☆51Updated 10 months ago
• cmu-phil / example-causal-datasets
  Example causal datasets with consistent formatting and ground truth
  ☆83Updated last month
• automl / TransformersCanDoBayesianInference
  Official Implementation of "Transformers Can Do Bayesian Inference", the PFN paper
  ☆217Updated 7 months ago
• paras2612 / CauseBox
  Causal inference is a critical task in various fields such as healthcare,economics, marketing and education. Recently, there have beensig…
  ☆21Updated 3 years ago