Search Results for author: Anubhav Jain

Found 14 papers, 5 papers with code

Enhancing Power Prediction of Photovoltaic Systems: Leveraging Dynamic Physical Model for Irradiance-to-Power Conversion

1 code implementation19 Feb 2024 Baojie Li, Xin Chen, Anubhav Jain

This dynamic model, periodically-updated (as short as daily), can closely capture the actual health status, enabling precise power estimation.

Alpha-wolves and Alpha-mammals: Exploring Dictionary Attacks on Iris Recognition Systems

no code implementations20 Nov 2023 Sudipta Banerjee, Anubhav Jain, Zehua Jiang, Nasir Memon, Julian Togelius, Arun Ross

A dictionary attack in a biometric system entails the use of a small number of strategically generated images or templates to successfully match with a large number of identities, thereby compromising security.

Iris Recognition

Matbench Discovery -- A framework to evaluate machine learning crystal stability predictions

2 code implementations28 Aug 2023 Janosh Riebesell, Rhys E. A. Goodall, Philipp Benner, Yuan Chiang, Bowen Deng, Alpha A. Lee, Anubhav Jain, Kristin A. Persson

The top 3 models are UIPs, the winning methodology for ML-guided materials discovery, achieving F1 scores of ~0. 6 for crystal stability classification and discovery acceleration factors (DAF) of up to 5x on the first 10k most stable predictions compared to dummy selection from our test set.

Formation Energy

Fair GANs through model rebalancing for extremely imbalanced class distributions

no code implementations16 Aug 2023 Anubhav Jain, Nasir Memon, Julian Togelius

We do so by generating balanced data from an existing imbalanced deep generative model using an evolutionary algorithm and then using this data to train a balanced generative model.

Fairness Generative Adversarial Network

Zero-shot racially balanced dataset generation using an existing biased StyleGAN2

1 code implementation12 May 2023 Anubhav Jain, Nasir Memon, Julian Togelius

Facial recognition systems have made significant strides thanks to data-heavy deep learning models, but these models rely on large privacy-sensitive datasets.

Face Recognition

Extracting Structured Seed-Mediated Gold Nanorod Growth Procedures from Literature with GPT-3

no code implementations26 Apr 2023 Nicholas Walker, John Dagdelen, Kevin Cruse, SangHoon Lee, Samuel Gleason, Alexander Dunn, Gerbrand Ceder, A. Paul Alivisatos, Kristin A. Persson, Anubhav Jain

To that end, we present an approach using the powerful GPT-3 language model to extract structured multi-step seed-mediated growth procedures and outcomes for gold nanorods from unstructured scientific text.

Language Modelling Relation Extraction

Structured information extraction from complex scientific text with fine-tuned large language models

no code implementations10 Dec 2022 Alexander Dunn, John Dagdelen, Nicholas Walker, SangHoon Lee, Andrew S. Rosen, Gerbrand Ceder, Kristin Persson, Anubhav Jain

Here, we present a simple sequence-to-sequence approach to joint named entity recognition and relation extraction for complex hierarchical information in scientific text.

Language Modelling Large Language Model +4

A Dataless FaceSwap Detection Approach Using Synthetic Images

1 code implementation5 Dec 2022 Anubhav Jain, Nasir Memon, Julian Togelius

Face swapping technology used to create "Deepfakes" has advanced significantly over the past few years and now enables us to create realistic facial manipulations.

DeepFake Detection Face Swapping

Dictionary Attacks on Speaker Verification

no code implementations24 Apr 2022 Mirko Marras, Pawel Korus, Anubhav Jain, Nasir Memon

In this paper, we propose dictionary attacks against speaker verification - a novel attack vector that aims to match a large fraction of speaker population by chance.

Speaker Verification Voice Cloning

Benchmarking Materials Property Prediction Methods: The Matbench Test Set and Automatminer Reference Algorithm

no code implementations2 May 2020 Alexander Dunn, Qi. Wang, Alex Ganose, Daniel Dopp, Anubhav Jain

The reference algorithm, Automatminer, is a highly-extensible, fully-automated ML pipeline for predicting materials properties from materials primitives (such as composition and crystal structure) without user intervention or hyperparameter tuning.

Materials Science Computational Physics

A critical examination of compound stability predictions from machine-learned formation energies

2 code implementations28 Jan 2020 Christopher J. Bartel, Amalie Trewartha, Qi. Wang, Alex Dunn, Anubhav Jain, Gerbrand Ceder

By testing seven machine learning models for formation energy on stability predictions using the Materials Project database of DFT calculations for 85, 014 unique chemical compositions, we show that while formation energies can indeed be predicted well, all compositional models perform poorly on predicting the stability of compounds, making them considerably less useful than DFT for the discovery and design of new solids.

Materials Science Computational Physics

Linking plastic heterogeneity of bulk metallic glasses to quench-in structural defects with machine learning

no code implementations7 Apr 2019 Qi. Wang, Anubhav Jain

When metallic glasses are subjected to mechanical loads, the plastic response of atoms is heterogeneous.

Materials Science Computational Physics

On Detecting GANs and Retouching based Synthetic Alterations

no code implementations26 Jan 2019 Anubhav Jain, Richa Singh, Mayank Vatsa

For distinguishing between real images and images generated using GANs, the proposed algorithm yields an accuracy of 99. 83%.

Face Recognition

Cannot find the paper you are looking for? You can Submit a new open access paper.