A game theoretic approach to explain the output of any machine learning model.

Handout for the tutorial "Creating publication-quality figures with matplotlib"

Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

ADC Performance Survey (ISSCC & VLSI Circuit Symposium)

DeepTrack2 is a modular Python library for generating, manipulating, and analyzing image data pipelines for machine learning and experimental imaging.

Python control of micro-manager for customized data acquisition

GPU-accelerated RCWA with automatic differentiation

📐 Workshop material for optical inverse design and automatic differentiation

A generative model for computing electromagnetic field solutions

Code and data to reproduce analyses in Biswas et al. (2020) "Low-N protein engineering with data-efficient deep learning".

DNA 5mC methylation detection from Dorado or Guppy basecalled Oxford Nanopore reads

Signal based nanopore RNA demultiplexing with convolutional neural networks

Gentle introduction and demo of the adjoint variable method for electromagnetic inverse design

Simulation and optimization of dielectric metalens with Tidy3D

PiSCAT is a python-based package with a graphical user interface for performing high-performance analysis on a variety of iSCAT measurements.

direct RNA nanopore sequencing barcode design and demultiplexing

An m6A-aware basecalling model to detect m6A modifications at single nucleotide resolution in individual reads (Cruciani, Delgado-Tejedor, Pryszcz et al., BioRxiv 2023)

Super-fast and accurate demultiplexing of direct RNA-seq runs.

Codes and results from ONT dRNA benchmarking

Code repository for 2019 NanoporeTERs paper.