st--'s repositories

annotate-equations

LaTeX package and annotated examples for annotating equations using TikZ.

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interactive-gp-visualization

Interactive visualization of Gaussian processes

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vbpp

Variational Bayes for Point Processes: implementation of Lloyd et al. (2015) on top of GPflow

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beamer-lecture-template-example

Template structure for consistent LaTeX/Beamer slides&handouts

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tikzplotlib

:bar_chart: Save matplotlib figures as TikZ/PGFplots for smooth integration into LaTeX.

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Aalto-pedagogy-intro--learning-feedback

Learning material on "Feedback" for Aalto Pedagogy Intro course

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active-bayesian-causal-inference

Active Bayesian Causal Inference (Neurips'22)

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algorithmic-efficiency

MLCommons Algorithmic Efficiency is a benchmark and competition measuring neural network training speedups due to algorithmic improvements in both training algorithms and models.

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blacktex

:black_heart: Cleans up your LaTeX files.

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dibs

DiBS: Differentiable Bayesian Structure Learning, NeurIPS 2021

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Distributions.jl

A Julia package for probability distributions and associated functions.

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doomemacs

An Emacs framework for the stubborn martian hacker

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Enzyme.jl

Julia bindings for the Enzyme automatic differentiator

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GPJax

Gaussian processes in JAX.

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gpytorch

A highly efficient and modular implementation of Gaussian Processes in PyTorch

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obsidian-tasks

Task management for the Obsidian knowledge base.

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online_vargp

Online variational GPs

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orthogonal-additive-gaussian-processes

Light-weighted code for Orthogonal Additive Gaussian Processes

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ray

Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

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ray-tune-slurm-demo

Testing ray tune with slurm batch submission and optuna and wandb

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reproducible-research-project-template

Template for writing a reproducible academic paper

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svelte-collapsible

A collection of high-level Svelte components designed for expanding and collapsing content.

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trieste

A Bayesian optimization toolbox built on TensorFlow

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v89

Proceedings of AISTATS 2019

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vargp

Variational Auto-Regressive Gaussian Processes for Continual Learning

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