jakesherman
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An interactive NVIDIA-GPU process viewer and beyond, the one-stop solution for GPU process management.
This repository consolidates my teaching material for "Causal Machine Learning".
A beautiful, simple, clean, and responsive Jekyll theme for academics
clean, simple and fast access to public hydrology and climatology data.
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
Uplift modeling and causal inference with machine learning algorithms
Extensive tutorials for learning how to build deep learning models for causal inference (HTE) using selection on observables in Tensorflow 2 and Pytorch.
Dataframes powered by a multithreaded, vectorized query engine, written in Rust
The long missing library for python confidence intervals
A scikit-learn-compatible module to estimate prediction intervals and control risks based on conformal predictions.
An extension of LightGBM to probabilistic modelling
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its go…
Official code for "DaisyRec 2.0: Benchmarking Recommendation for Rigorous Evaluation" (TPAMI2022) and "Are We Evaluating Rigorously? Benchmarking Recommendation for Reproducible Evaluation and Fair…
Statistical package in Python based on Pandas
Code repository of the paper Learning Long-Term Dependencies in Irregularly-Sampled Time Series
A Python/C++ implementation of Bayesian Factorization Machines
A library for factorization machines and polynomial networks for classification and regression in Python.
A garden for scikit-learn compatible trees
A python library to build Model Trees with Linear Models at the leaves.
A python package for non parametric Mann Kendall family of trend tests.
Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network, in Pytorch
Tensor package with focus in low rank approximations.
Transformers4Rec is a flexible and efficient library for sequential and session-based recommendation and works with PyTorch.
Accompanying code for the paper Performance of Hyperbolic Geometry Models on Top-N Recommendation Tasks, accepted at ACM RecSys 2020.
Accompanying code for reproducing experiments from the HybridSVD paper. Preprint is available at https://arxiv.org/abs/1802.06398.
A pytorch port of google-research/google-research/robust_loss/
Binary and Categorical Focal loss implementation in Keras.