mnarayan

deepmind-research

This repository contains implementations and illustrative code to accompany DeepMind publications

EPIJudge

EPI Judge - Preview Release

executorch

On-device AI across mobile, embedded and edge for PyTorch

PromptKG

PromptKG Family: a Gallery of Prompt Learning & KG-related research works, toolkits, and paper-list.

specter

SPECTER: Document-level Representation Learning using Citation-informed Transformers

evodiff

Generation of protein sequences and evolutionary alignments via discrete diffusion models

reward-bench

RewardBench: the first evaluation tool for reward models.

mmrm

Mixed Models for Repeated Measures (MMRM) in R.

syntheseus

Package for Retrosynthetic Planning

proxmin

Proximal optimization in pure python

antibioticsai

Supporting code for the paper "Discovery of a structural class of antibiotics with explainable deep learning"

RetMol

A new retrieval-based framework for controllable molecule generation.

PA-Graph-Transformer

ProxGradPytorch

PyTorch implementation of Proximal Gradient Algorithms a la Parikh and Boyd (2014). Useful for Auto-Sizing (Murray and Chiang 2015, Murray et al. 2019).

tn_test

post-clustering differential expression test

FRoGS

Functional Embedding of Gene Signatures

CausalRL

Implementation of "Dynamic Causal Effects Evaluation in A/B Testing with a Reinforcement Learning Framework" (JASA 2023)

SPECTRA

Spectral Framework For AI Model Evaluation

MTB-CNN

CNN models for antibiotic resistance prediction in M. tuberculosis genomes. From Green & Yoon et al (forthcoming)

RATE

Code for Variable Selection in Black Box Methods with RelATive cEntrality (RATE) Measures

DeepCausalPV-master

CODE-AE

Coherent Deconfounding Autoencoder (CODE-AE) can extract both common biological signals shared by incoherent samples and private representations unique to each data set, transfer knowledge learned from cell line data to tissue data, and separate confounding factors from them

multitask-toxicity

Repository for Multitask Toxicity with Contrastive Explanation

quarto-crc

A Quarto example of Chapman & Hall/CRC books

Hasel_et_al

CODEX

COunterfactual Deep learning for the in-silico EXploration of cancer cell line perturbations

cryptic-mic

Code used to analyze data and create plots for "Quantitative measurement of antibiotic resistance in Mycobacterium tuberculosis reveals genetic determinants of resistance and susceptibility in a target gene approach"

Caravaca2022

Code for Caravaca et al, 2022, PNAS

ALEC_stats

This is a temporary repository for writing python functions for ALEC platform.

tmsr

Biomarkers for TB Treatment Monitoring