On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,742 papers · 148 categories

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7 results for “GPyTorch”

Bayesian Hyperparameter Optimization with BoTorch, GPyTorch and Axcs.LG

Bayesian optimization finds best hyperparameters for deep learning models.

problem Finding optimal hyperparameters in high-dimensional space.

method Bayesian optimization, Gaussian processes, and adaptive experimentation.

result Ax, BoTorch, and GPyTorch provide a powerful and simple framework for hyperparameter optimization.

Bayesian optimization hyperparameter tuning Gaussian processes Ax BoTorch

2019-12-11abs ↗pdf ↗

UncertaintyPlayground: A Fast and Simplified Python Library for Uncertainty Estimationstat.ML

UncertaintyPlayground simplifies uncertainty estimation in Python.

problem Uncertainty estimation in supervised learning tasks.

method Sparse and Variational Gaussian Process Regressions for normally distributed outcomes, Mixed Density Networks for mixed distributions.

result Fast and simplified uncertainty estimation through Python library.

uncertainty estimation supervised learning Python GPyTorch PyTorch

2023-10-23abs ↗pdf ↗

GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Accelerationcs.LG

Despite advances in scalable models, the inference tools used for Gaussian processes (GPs) have yet to fully capitalize on developments in computing hardware. We present an efficient and general approach to GP inference based on Blackbox Matrix-Matrix multiplication (BBMM). BBMM inference uses a modified batched versio…

2018-09-28abs ↗pdf ↗

A Quadrature Approach for General-Purpose Batch Bayesian Optimization via Probabilistic Liftingcs.LG

SOBER framework optimizes Bayesian optimization tasks efficiently.

problem Challenges in parallel Bayesian optimization.

method Probabilistic Lifting with Kernel Quadrature.

result Versatile and flexible batch Bayesian optimization.

Bayesian optimization batch optimization kernel quadrature probabilistic lifting parallelization

2024-04-18abs ↗pdf ↗

Gradients of Functions of Large Matricescs.LG

Efficiently differentiate functions of large matrices using new adjoint systems.

problem Differentiating functions of large matrices in scientific and probabilistic machine learning models.

method Deriving and implementing new adjoint systems for Lanczos and Arnoldi iterations in JAX.

result Efficient differentiation of PDEs, Gaussian process models, and Bayesian neural networks.

matrix differentiation Lanczos iteration Arnoldi iteration machine learning partial differential equations

2024-05-27abs ↗pdf ↗

Enhancing Corrosion Resistance of Aluminum Alloys Through AI and ML Modelingeess.SP

Study uses AI and ML to predict and optimize corrosion resistance of aluminum alloys.

problem Corrosion resistance of aluminum alloys in marine environments.

method Investigated two ML approaches: direct and inverse, using Random Forest, neural network, and Gaussian Process Regression.

result Gaussian Process Regression with hybrid kernel functions provided superior predictive performance.

Aluminum alloys Corrosion resistance Machine learning Random Forest Neural networks

2025-08-10abs ↗pdf ↗

A Framework for Nonstationary Gaussian Processes with Neural Network Parameterscs.LG

Flexible nonstationary Gaussian process with neural network parameters.

problem Limited expressiveness of stationary Gaussian processes.

method Nonstationary kernels with neural network parameters trained jointly.

result Better accuracy and log-score compared to stationary and hierarchical models.

Gaussian processes nonstationary kernels neural networks flexibility machine learning

2025-07-16abs ↗pdf ↗