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
  ☆141Updated 2 years ago
• wassname / attentive-neural-processes
  implementing "recurrent attentive neural processes" to forecast power usage (w. LSTM baseline, MCDropout)
  ☆98Updated 7 months ago
• kamilest / conformal-rnn
  Implementation for Stankevičiūtė et al. "Conformal time-series forecasting", NeurIPS 2021.
  ☆76Updated 11 months ago
• steveli / partial-encoder-decoder
  An encoder-decoder framework for learning from incomplete data
  ☆45Updated 2 years ago
• ahmedmalaa / Fourier-flows
  ☆18Updated 3 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
• sanatonek / time_series_explainability
  ☆62Updated 4 years ago
• edebrouwer / gru_ode_bayes
  Pytorch implementation of GRU-ODE-Bayes
  ☆230Updated 3 years ago
• mlech26l / ode-lstms
  Code repository of the paper Learning Long-Term Dependencies in Irregularly-Sampled Time Series
  ☆119Updated 2 years ago
• ayaabdelsalam91 / TS-Interpretability-Benchmark
  ☆91Updated 4 years ago
• boschresearch / Continuous-Recurrent-Units
  ☆68Updated 2 years ago
• TeaPearce / Deep_Learning_Prediction_Intervals
  ICML paper 'High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach'
  ☆91Updated 5 years ago
• edebrouwer / latentCCM
  Implementation of the Latent CCM paper
  ☆16Updated last year
• mbohlkeschneider / gluon-ts
  GluonTS - Probabilistic Time Series Modeling in Python
  ☆52Updated 3 years ago
• pmorenoz / HetMOGP
  Heterogeneous Multi-output Gaussian Processes
  ☆53Updated 5 years ago
• tgcsaba / GPSig
  Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
  ☆48Updated 2 years ago
• loeweX / AmortizedCausalDiscovery
  Code for the paper: Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data
  ☆217Updated 3 years ago
• YoungseogChung / calibrated-quantile-uq
  Repository for Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification (NeurIPS 2024)
  ☆44Updated 11 months ago
• hamrel-cxu / EnbPI
  Official code for: Conformal prediction interval for dynamic time-series (conference, ICML 21 Long Presentation) AND Conformal prediction…
  ☆126Updated last year
• HansikaPH / time-series-forecasting
  Recurrent Neural Network Implementations for Time Series Forecasting
  ☆75Updated 3 years ago
• aangelopoulos / conformal-time-series
  Conformal prediction for time-series applications.
  ☆123Updated last year
• BorgwardtLab / Set_Functions_for_Time_Series
  Repository of the ICML 2020 paper "Set Functions for Time Series"
  ☆126Updated 4 years ago
• yromano / cqr
  Conformalized Quantile Regression
  ☆290Updated 3 years ago
• automl / TransformersCanDoBayesianInference
  Official Implementation of "Transformers Can Do Bayesian Inference", the PFN paper
  ☆237Updated last year
• HerreraKrachTeichmann / NJODE
  code for "Neural Jump Ordinary Differential Equations"
  ☆30Updated 2 years ago
• mbilos / neural-flows-experiments
  Experiments for Neural Flows paper
  ☆98Updated 3 years ago
• jambo6 / online-neural-cdes
  Code for: "Neural Controlled Differential Equations for Online Prediction Tasks"
  ☆38Updated 3 years ago
• patrick-kidger / generalised_shapelets
  Code for "Generalised Interpretable Shapelets for Irregular Time Series"
  ☆57Updated 2 years ago
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆43Updated last year