Pinned Repositories
DeepUQ
Bayesian Uncertainty Quantification by Deep Generative Model
BestPractices
Best Practices for using ML in Science
LFI-ressources
a compilation of ressources for likelihood free inference (LFI undergrad project)
MADLens
a differentiable lensing simulator
ML_Lectures
MnuLFI
throwing LFI on massiveNus sims
PAE
Probabilistic Auto-Encoder
PAE-ablation
ablation studies between PAE and flow-VAE
PytorchPAE
Implemenations of PAE in pytorch
SAR-landslide-detection-pretraining
Repository for the paper "SAR-based landslide classification pretraining leads to better segmentation"
VMBoehm's Repositories
VMBoehm/PAE
Probabilistic Auto-Encoder
VMBoehm/SAR-landslide-detection-pretraining
Repository for the paper "SAR-based landslide classification pretraining leads to better segmentation"
VMBoehm/MADLens
a differentiable lensing simulator
VMBoehm/BestPractices
Best Practices for using ML in Science
VMBoehm/PytorchPAE
Implemenations of PAE in pytorch
VMBoehm/PAE-ablation
ablation studies between PAE and flow-VAE
VMBoehm/ML_Lectures
VMBoehm/N3AS_Project_Malika
neutrino dataset classification
VMBoehm/JobSearchScripts
VMBoehm/LSSTC-DSFP-Sessions
Lecture slides, Jupyter notebooks, and other material from the LSSTC Data Science Fellowship Program
VMBoehm/MediumArticles
VMBoehm/pca-classifier
classification with Gaussian likelihood ratios
VMBoehm/arxivscraper
A python module to scrape arxiv.org for specific date range and categories
VMBoehm/GIS
Biweis GIS code adapted
VMBoehm/kernel_regression
Implementation of Nadaraya-Watson kernel regression with automatic bandwidth selection compatible with sklearn.
VMBoehm/MassRecon
lensing reconstruction
VMBoehm/ML-Tutorials
Machine Learning Tutorials
VMBoehm/N3ASProject_Annie
Hardening parameter inference from gravitational lensing against baryonic physics
VMBoehm/optuna-examples
Examples for https://github.com/optuna/optuna
VMBoehm/OptunaTutorial
Hyperparameter Optimization Tutorial
VMBoehm/personal-website
Code that'll help you kickstart a personal website that showcases your work as a software developer.
VMBoehm/pymc
Bayesian Modeling and Probabilistic Programming in Python
VMBoehm/PythonicTextAnalysis
tools for scraping and analysing text data in python
VMBoehm/Revealing-Ferroelectric-Switching-Character-Using-Deep-Recurrent-Neural-Networks
The ability to manipulate domains and domain walls underpins function in a range of next-generation applications of ferroelectrics. While there have been demonstrations of controlled nanoscale manipulation of domain structures to drive emergent properties, such approaches lack an internal feedback loop required for automation. Here, using a deep sequence-to-sequence autoencoder we automate the extraction of features of nanoscale ferroelectric switching from multichannel hyperspectral band-excitation piezoresponse force microscopy of tensile-strained PbZr0.2Ti0.8O3 with a hierarchical domain structure. Using this approach, we identify characteristic behavior in the piezoresponse and cantilever resonance hysteresis loops, which allows for the classification and quantification of nanoscale-switching mechanisms. Specifically, we are able to identify elastic hardening events which are associated with the nucleation and growth of charged domain walls. This work demonstrates the efficacy of unsupervised neural networks in learning features of the physical response of a material from nanoscale multichannel hyperspectral imagery and provides new capabilities in leveraging multimodal in operando spectroscopies and automated control for the manipulation of nanoscale structures in materials.
VMBoehm/SDSS_PAE
VMBoehm/SINF
Sliced Iterative Generator (SIG) & Gaussianizing Iterative Slicing (GIS)
VMBoehm/Spectra_PAE
Probabilsitic autoencoder for galaxy spectra
VMBoehm/uncertainty-baselines
High-quality implementations of standard and SOTA methods on a variety of tasks.
VMBoehm/UndergradStudentProjects
VMBoehm/VMBoehm.github.io
website