Calculate torsional response for Closed-Thin Walled and Open Thin-Walled theory, then compare with experimental data.

Experimental study and analysis on the effect of using a wide range of different supply voltage values on the reliability, latency, and retention characteristics of DDR3L DRAM SO-DIMMs

A flexible and modular Structure Optimization suite for combining experimental data with energy simulations to create atomic structures.

LabNotebook is a tool that allows you to flexibly monitor, record, save, and query all your machine learning experiments.

Structure learning for Bayesian networks using the CCDr algorithm.

Rapid Data Import Environmnent

Reinforcement Learning Course Project - IIT Bombay Fall 2018

AspectOCL experiment data

Making transport analysis accessible for experimental scientists.

A collection of behavioral data sets & some functions for extracting semantic associations and network structures from term-feature matrices.

Supplementary data for "A Bayesian Sequential Learning Framework to Parameterise Continuum Models of Melanoma Invasion into Human Skin" Bull Math Biol 2019

Processing of IV data obtained in experiments - rescaling, centering, converting to RI.

A web-based platform to facilitate experimental data understanding and communication, which combines an efficient backend DBMS for storage and querying with web-based functions for schema design, data entry/management, as well as dynamic data analysis and visualization.

Processing of experimental IV data - rescaling, centering, switch from I-V to R-I presentation.

Finding of convertion coefficient for further recalculation of probability (P) into the temperature (T).

Software for learning sparse Bayesian networks

Supplementary material for "Identifying density-dependent interactions in collective cell behaviour"

BEER determines an ECC code's parity-check matrix based on the uncorrectable errors it can cause. BEER targets Hamming codes that are used for DRAM on-die ECC but can be extended to apply to other linear block codes (e.g., BCH, Reed-Solomon). BEER is described in the 2020 MICRO paper by Patel et al.: https://arxiv.org/abs/2009.07985.

Code for exploring how we distribute our thoughts over time when we remember, using data from a naturalistic memory experiment.