Cryptanalysis of Physically Unclonable Functions
-
Updated
Jun 29, 2024 - Python
#
crps
Here are 23 public repositories matching this topic...
Ensemble price forecasting with volatility prediction (XGBoost on cached features). Multiple simulated paths per request; CRPS scoring for calibration and sharpness. Synthetic price data for options and portfolio analytics. Python, XGBoost, NumPy, Pandas, properscoring, Pyth API, PostgreSQL, Pydantic, Docker.
machine-learning docker-compose numpy ethereum pandas pytest xgboost btc financial-data volatility solana crps
-
Updated
Mar 13, 2026 - Python
Official pytorch implementation codes for NeurIPS-2023 accepted paper "Distributional Learning of Variational AutoEncoder: Application to Synthetic Data Generation"
-
Updated
Nov 22, 2023 - Python
Model stacking for predictive ensembles
-
Updated
Aug 24, 2026 - HTML
DINOv3 as a Frozen Encoder for CRPS-Oriented Probabilistic Rainfall Nowcasting (Neurips W4C Competition)
-
Updated
Nov 17, 2025 - Python
Distributional crypto-return forecasting via Wasserstein-geodesic extrapolation in quantile-function space. WGeo family wins 12/12 (asset × horizon) cells over 6.75y walk-forward CRPS vs GARCH and classical baselines. v0.4.
python research time-series bitcoin cryptocurrency econometrics forecasting wasserstein garch optimal-transport wasserstein-barycenter risk-management backtesting quantile-regression caviar financial-modeling crps diebold-mariano distributional-forecasting har-rv
-
Updated
Sep 22, 2026 - Python
Official implementation of 'Distributional Learning of Variational AutoEncoder: Application to Synthetic Data Generation' (DistVAE) with pytorch (NeurIPS 2023 accepted paper).
tabular-data mixed-type variational-autoencoder synthetic-data distributional-learning crps continuous-ranked-probability-score
-
Updated
Dec 19, 2024 - Jupyter Notebook
Interactive Streamlit dashboard to verify gridded rainfall/precipitation forecasts (deterministic & ensemble, NetCDF + GRIB2) against observations — POD/FAR/CSI/ETS/HSS, EDI/SEDI/EDS/SEDS, Brier/BSS/CRPS, FSS & CRA, reliability/ROC/rank/PIT/Taylor plots, per-cell score maps, bootstrap CIs, CSV/PNG export. Runs on bundled demo data.
python dashboard climate geospatial xarray netcdf meteorology grib rainfall hydrology precipitation probabilistic-forecasting forecast-verification numerical-weather-prediction streamlit crps spatial-verification ensemble-forecasting verification-metrics
-
Updated
Sep 21, 2026 - Python
Implementation of"Learning Quantile Functions for Temporal Point Processes with Recurrent Neural Splines" (@ AISTATS 2022)
-
Updated
Feb 21, 2022 - Python
Reproducibility artifact for 'Heads, Not Backbones: Output Heads Dominate Architectures on Fat-Tailed Returns' (arXiv:2606.30037)
time-series crps walk-forward density-forecasting arxiv-2606-30037 mixture-density fat-tailed-returns
-
Updated
Jul 1, 2026 - Python
Fast distributional random forests with CART, MMD, and sliced-Wasserstein splitting
python rust random-forest mmd uncertainty-quantification probabilistic-models quantile-regression random-forest-regression pyo3 distributional-regression probabilistic-regression maturin crps
-
Updated
Sep 13, 2026 - Python
Standalone implementations and reproducible evaluation harness for Simfolio's 175 forecasting models for out-of-sample research and validation.
-
Updated
Sep 10, 2026 - Python
Distributional forecasts scored with CRPS and PIT calibration, plus block-bootstrap tests that separate leaderboard skill from luck
-
Updated
Jul 27, 2026 - Python
Demand forecasts whose uncertainty ranges hold when conditions shift, turned into a staffing number at a chosen service level: hierarchical probabilistic forecasting, adaptive conformal intervals, MinT reconciliation and a newsvendor decision layer.
python machine-learning time-series reproducible-research capacity-planning open-data lightgbm uncertainty-quantification operations-research demand-forecasting conformal-prediction probabilistic-forecasting hierarchical-forecasting crps forecast-reconciliation healthcare-analytics foundation-models newsvendor timesfm neural-forecasting
-
Updated
Sep 20, 2026 - Python
Links calibrated deep probabilistic forecasting to reinforcement-learning monetary policy through a shared belief state. A CRPS-trained multi-scale LSTM supplies time-varying uncertainty to a POMDP central bank; realistic beliefs collapse the learned Taylor coefficient from ~1.1 to ~0.02 across every seed under both PPO and SAC.
reinforcement-learning deep-learning pytorch calibration lstm sac pomdp macroeconomics ppo monetary-policy probabilistic-forecasting crps new-keynesian
-
Updated
Aug 17, 2026 - Jupyter Notebook
R2 — LLM calibration benchmark: 18-scenario Florida rainfall eval crossing a specificity gradient with a seasonal gradient, CRPS scoring, and ground-truth-free self-consistency checks.
-
Updated
Jul 31, 2026 - Python
Training-free probabilistic time-series forecasting with Conformal Seasonal Pools (CSP): a numpy-only empirical sampler with quantiles, prediction intervals, and rolling-origin backtesting.
python machine-learning time-series numpy forecasting uncertainty-quantification time-series-forecasting conformal-prediction probabilistic-forecasting crps
-
Updated
Jun 10, 2026 - Jupyter Notebook
A modern, privacy-focused companion app designed to help people with Complex Regional Pain Syndrome (CRPS) document symptoms, identify patterns, and better understand their daily condition.
-
Updated
Sep 22, 2026 - TypeScript
Add this topic to your repo
To associate your repository with the crps topic, visit your repo's landing page and select "manage topics."