Alternatives and similar repositories for AdaFNN

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

• ratschlab / GP-VAE
  TensorFlow implementation for the GP-VAE model described in https://arxiv.org/abs/1907.04155
  ☆142Updated 2 years ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆75Updated 3 years ago
• 000Justin000 / torchdiffeq
  Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.
  ☆63Updated 4 years ago
• ahmedmalaa / Fourier-flows
  ☆18Updated 3 years ago
• kamilest / conformal-rnn
  Implementation for Stankevičiūtė et al. "Conformal time-series forecasting", NeurIPS 2021.
  ☆77Updated last year
• steveli / partial-encoder-decoder
  An encoder-decoder framework for learning from incomplete data
  ☆45Updated 2 years ago
• hamrel-cxu / EnbPI
  Official code for: Conformal prediction interval for dynamic time-series (conference, ICML 21 Long Presentation) AND Conformal prediction…
  ☆128Updated last year
• wassname / attentive-neural-processes
  implementing "recurrent attentive neural processes" to forecast power usage (w. LSTM baseline, MCDropout)
  ☆99Updated 7 months ago
• sanatonek / time_series_explainability
  ☆62Updated 4 years ago
• YoungseogChung / calibrated-quantile-uq
  Repository for Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification (NeurIPS 2024)
  ☆44Updated 11 months ago
• ayaabdelsalam91 / TS-Interpretability-Benchmark
  ☆91Updated 4 years ago
• mlech26l / ode-lstms
  Code repository of the paper Learning Long-Term Dependencies in Irregularly-Sampled Time Series
  ☆119Updated 2 years ago
• JonathanCrabbe / Dynamask
  This repository contains the implementation of Dynamask, a method to identify the features that are salient for a model to issue its pred…
  ☆75Updated 3 years ago
• patrick-kidger / generalised_shapelets
  Code for "Generalised Interpretable Shapelets for Irregular Time Series"
  ☆57Updated 2 years ago
• edebrouwer / gru_ode_bayes
  Pytorch implementation of GRU-ODE-Bayes
  ☆231Updated 3 years ago
• TeaPearce / Deep_Learning_Prediction_Intervals
  ICML paper 'High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach'
  ☆92Updated 5 years ago
• boschresearch / Continuous-Recurrent-Units
  ☆68Updated 2 years ago
• tiskw / random-fourier-features
  Implementation of random Fourier features for kernel method, like support vector machine and Gaussian process model
  ☆102Updated last year
• aangelopoulos / conformal-time-series
  Conformal prediction for time-series applications.
  ☆127Updated last year
• XAI-360 / TSCL
  Contrastive Learning for Time Series
  ☆40Updated 2 years ago
• mbilos / neural-flows-experiments
  Experiments for Neural Flows paper
  ☆99Updated 3 years ago
• pamattei / miwae
  Implementation of the MIWAE method for deep generative modelling of incomplete data sets.
  ☆41Updated last year
• yantijin / ScoreGradPred
  Code for *ScoreGrad: Multivariate Probabilistic Time Series Forecasting with Continuous Energy-based Generative Models*
  ☆87Updated 9 months ago
• MarkPKCollier / MissingDataVAEs
  ☆19Updated 5 years ago
• causalens / cdml-neurips2020
  This repository captures source code and data sets for our paper at the Causal Discovery & Causality-Inspired Machine Learning Workshop a…
  ☆62Updated last year
• iancovert / Neural-GC
  Granger causality discovery for neural networks.
  ☆230Updated 4 years ago
• HerreraKrachTeichmann / NJODE
  code for "Neural Jump Ordinary Differential Equations"
  ☆30Updated 2 years ago
• mbohlkeschneider / gluon-ts
  GluonTS - Probabilistic Time Series Modeling in Python
  ☆52Updated 4 years ago
• AWehenkel / UMNN
  Implementation of Unconstrained Monotonic Neural Network and the related experiments. These architectures are particularly useful for mod…
  ☆125Updated 11 months ago
• BorgwardtLab / Set_Functions_for_Time_Series
  Repository of the ICML 2020 paper "Set Functions for Time Series"
  ☆126Updated 4 years ago