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
  ☆143Updated 2 years ago
• edebrouwer / gru_ode_bayes
  Pytorch implementation of GRU-ODE-Bayes
  ☆233Updated 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
• wassname / attentive-neural-processes
  implementing "recurrent attentive neural processes" to forecast power usage (w. LSTM baseline, MCDropout)
  ☆100Updated 10 months ago
• mlds-lab / interp-net
  Code for "Interpolation-Prediction Networks for Irregularly Sampled Time Series", ICLR 2019.
  ☆94Updated last year
• mlech26l / ode-lstms
  Code repository of the paper Learning Long-Term Dependencies in Irregularly-Sampled Time Series
  ☆121Updated 2 years ago
• BorgwardtLab / Set_Functions_for_Time_Series
  Repository of the ICML 2020 paper "Set Functions for Time Series"
  ☆129Updated 4 years ago
• sanatonek / time_series_explainability
  ☆62Updated 4 years ago
• ahmedmalaa / Fourier-flows
  ☆18Updated 4 years ago
• ayaabdelsalam91 / TS-Interpretability-Benchmark
  ☆91Updated 4 years ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆75Updated 3 years ago
• patrick-kidger / generalised_shapelets
  Code for "Generalised Interpretable Shapelets for Irregular Time Series"
  ☆57Updated 2 years ago
• hamrel-cxu / EnbPI
  Official code for: Conformal prediction interval for dynamic time-series (conference, ICML 21 Long Presentation) AND Conformal prediction…
  ☆129Updated 2 years ago
• 000Justin000 / torchdiffeq
  Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.
  ☆64Updated 4 years ago
• boschresearch / Continuous-Recurrent-Units
  ☆69Updated 2 years ago
• probabilistic-learning / HI-VAE
  ☆92Updated 2 years ago
• sakhanna / SRU_for_GCI
  Statistical Recurrent Unit based time series generative models for detecting nonlinear Granger causality
  ☆35Updated 5 years ago
• loeweX / AmortizedCausalDiscovery
  Code for the paper: Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data
  ☆223Updated 3 years ago
• iancovert / Neural-GC
  Granger causality discovery for neural networks.
  ☆235Updated 4 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
• mbohlkeschneider / gluon-ts
  GluonTS - Probabilistic Time Series Modeling in Python
  ☆52Updated 4 years ago
• rajatsen91 / deepglo
  This repository contains code for the paper: https://arxiv.org/abs/1905.03806. It also contains scripts to reproduce the results in the p…
  ☆170Updated 5 years ago
• yromano / cqr
  Conformalized Quantile Regression
  ☆301Updated 3 years ago
• TeaPearce / Deep_Learning_Prediction_Intervals
  ICML paper 'High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach'
  ☆94Updated 5 years ago
• aangelopoulos / conformal-time-series
  Conformal prediction for time-series applications.
  ☆131Updated 2 years ago
• YoungseogChung / calibrated-quantile-uq
  Repository for Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification (NeurIPS 2024)
  ☆44Updated last year
• pmorenoz / HetMOGP
  Heterogeneous Multi-output Gaussian Processes
  ☆54Updated 5 years ago
• HansikaPH / time-series-forecasting
  Recurrent Neural Network Implementations for Time Series Forecasting
  ☆75Updated 4 years ago
• FelixOpolka / Deep-Gaussian-Process
  🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0
  ☆25Updated last year