Vikas Garg

Vikas Garg

Massachusetts Institute of Technology

H-index: 14

North America-United States

About Vikas Garg

Vikas Garg, With an exceptional h-index of 14 and a recent h-index of 13 (since 2020), a distinguished researcher at Massachusetts Institute of Technology, specializes in the field of Machine Learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

Going beyond persistent homology using persistent homology

Generative AI for graph-based drug design: Recent advances and the way forward

Employing Federated Learning for Training Autonomous HVAC Systems

Graph4GUI: Graph Neural Networks for Representing Graphical User Interfaces

ClimODE: Climate and Weather Forecasting with Physics-informed Neural ODEs

Field-based Molecule Generation

Forked Diffusion for Conditional Graph Generation

Meta Compression: Learning to compress Deep Neural Networks

Vikas Garg Information

University

Position

(MIT)

Citations(all)

1276

Citations(since 2020)

989

Cited By

533

hIndex(all)

14

hIndex(since 2020)

13

i10Index(all)

18

i10Index(since 2020)

14

Email

University Profile Page

Massachusetts Institute of Technology

Google Scholar

View Google Scholar Profile

Vikas Garg Skills & Research Interests

Machine Learning

Top articles of Vikas Garg

Title

Journal

Author(s)

Publication Date

Going beyond persistent homology using persistent homology

Advances in Neural Information Processing Systems

Johanna Immonen

Amauri Souza

Vikas Garg

2024/2/13

Generative AI for graph-based drug design: Recent advances and the way forward

Vikas Garg

2024/2/1

Employing Federated Learning for Training Autonomous HVAC Systems

arXiv preprint arXiv:2405.00389

Fredrik Hagström

Vikas Garg

Fabricio Oliveira

2024/5/1

Graph4GUI: Graph Neural Networks for Representing Graphical User Interfaces

arXiv preprint arXiv:2404.13521

Yue Jiang

Changkong Zhou

Vikas Garg

Antti Oulasvirta

2024/4/21

ClimODE: Climate and Weather Forecasting with Physics-informed Neural ODEs

arXiv preprint arXiv:2404.10024

Yogesh Verma

Markus Heinonen

Vikas Garg

2024/4/15

Field-based Molecule Generation

arXiv preprint arXiv:2402.15864

Alexandru Dumitrescu

Dani Korpela

Markus Heinonen

Yogesh Verma

Valerii Iakovlev

...

2024/2/24

Forked Diffusion for Conditional Graph Generation

Giangiacomo Mercatali

Yogesh Verma

Andre Freitas

Vikas Garg

2023/10/13

Meta Compression: Learning to compress Deep Neural Networks

Ashutosh Vaishnav

Ankit Khatri

Vikas Garg

Mario Di Francesco

2023/10/13

Molecule Generation by Heterophilious Triple Flows

Haishan Wang

Arno Solin

Vikas Garg

2023/10/13

AbODE: Ab initio antibody design using conjoined ODEs

Yogesh Verma

Markus Heinonen

Vikas Garg

2023/7/3

Graph neural network autoencoders for efficient quantum circuit optimisation

arXiv preprint arXiv:2303.03280

Ioana Moflic

Vikas Garg

Alexandru Paler

2023/3/6

Streamlining Generative Models for Structure-Based Drug Design

Rafal Karczewski

Markus Heinonen

Vikas Garg

2023/10/13

Algebraic Positional Encodings

arXiv preprint arXiv:2312.16045

Konstantinos Kogkalidis

Jean-Philippe Bernardy

Vikas Garg

2023/12/26

Very large scale quantum circuit optimisation using alternative circuit representations

APS March Meeting Abstracts

Ioana Moflic

Vikas Garg

Alexandru Paler

2023

How well does Persistent Homology generalize on graphs?

Kirill Brilliantov

Amauri H Souza

Vikas Garg

2023/10/13

Compositional sculpting of iterative generative processes

Advances in neural information processing systems

Timur Garipov

Sebastiaan De Peuter

Ge Yang

Vikas Garg

Samuel Kaski

...

2023/12/15

Towards improving decoder performance with machine learned open quantum system simulations

APS March Meeting Abstracts

Arshpreet Maan

Vikas Garg

Alexandru Paler

2023

Twinned Interventional Flows

Linda Hemmann

Vikas Garg

2023/10/13

ClimODE: Climate Forecasting With Physics-informed Neural ODEs

Yogesh Verma

Markus Heinonen

Vikas Garg

2023/10/13

Modular flows: Differential molecular generation

Advances in neural information processing systems

Yogesh Verma

Samuel Kaski

Markus Heinonen

Vikas Garg

2022/12/6

See List of Professors in Vikas Garg University(Massachusetts Institute of Technology)