Vikas Garg

According to our database, Vikas Garg authored at least 55 papers between 2009 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

Diffusion Models as Cartoonists! The Curious Case of High Density Regions.

Rafal Karczewski, Markus Heinonen, Vikas Garg

CoRR, 2024

Diffusion Twigs with Loop Guidance for Conditional Graph Generation.

Giangiacomo Mercatali, Yogesh Verma, André Freitas, Vikas Garg

CoRR, 2024

ACE: Abstractions for Communicating Efficiently.

Jonathan D. Thomas, Andrea Silvi, Devdatt P. Dubhashi, Vikas Garg, Moa Johansson

CoRR, 2024

What Ails Generative Structure-based Drug Design: Too Little or Too Much Expressivity?

Rafal Karczewski, Samuel Kaski, Markus Heinonen, Vikas Garg

CoRR, 2024

Alignment is Key for Applying Diffusion Models to Retrosynthesis.

Najwa Laabid, Severi Rissanen, Markus Heinonen, Arno Solin, Vikas Garg

CoRR, 2024

Heteroscedastic Preferential Bayesian Optimization with Informative Noise Distributions.

Marshal Arijona Sinaga, Julien Martinelli, Vikas Garg, Samuel Kaski

CoRR, 2024

Employing Federated Learning for Training Autonomous HVAC Systems.

Fredrik Hagström, Vikas Garg, Fabricio Oliveira

CoRR, 2024

Field-based Molecule Generation.

Alexandru Dumitrescu, Dani Korpela, Markus Heinonen, Yogesh Verma, Valerii Iakovlev, Vikas Garg, Harri Lähdesmäki

CoRR, 2024

Topological Neural Networks go Persistent, Equivariant, and Continuous.

Yogesh Verma, Amauri H. Souza, Vikas Garg

Proceedings of the Forty-first International Conference on Machine Learning, 2024

On the Generalization of Equivariant Graph Neural Networks.

Rafal Karczewski, Amauri H. Souza, Vikas Garg

Proceedings of the Forty-first International Conference on Machine Learning, 2024

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

Yogesh Verma, Markus Heinonen, Vikas Garg

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Graph4GUI: Graph Neural Networks for Representing Graphical User Interfaces.

Yue Jiang, Changkong Zhou, Vikas Garg, Antti Oulasvirta

Proceedings of the CHI Conference on Human Factors in Computing Systems, 2024

2023

Algebraic Positional Encodings.

Konstantinos Kogkalidis, Jean-Philippe Bernardy, Vikas Garg

CoRR, 2023

Going beyond persistent homology using persistent homology.

Johanna Immonen, Amauri H. Souza, Vikas Garg

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Compositional Sculpting of Iterative Generative Processes.

Timur Garipov, Sebastiaan De Peuter, Ge Yang, Vikas Garg, Samuel Kaski, Tommi S. Jaakkola

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

AbODE: Ab initio antibody design using conjoined ODEs.

Yogesh Verma, Markus Heinonen, Vikas Garg

Proceedings of the International Conference on Machine Learning, 2023

2022

Why GANs are overkill for NLP.

David Alvarez-Melis, Vikas Garg, Adam Tauman Kalai

CoRR, 2022

Modular Flows: Differential Molecular Generation.

Yogesh Verma, Samuel Kaski, Markus Heinonen, Vikas Garg

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Provably expressive temporal graph networks.

Amauri H. Souza, Diego Mesquita, Samuel Kaski, Vikas Garg

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Symmetry-induced Disentanglement on Graphs.

Giangiacomo Mercatali, André Freitas, Vikas Garg

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Are GANs overkill for NLP?

David Alvarez-Melis, Vikas Garg, Adam Kalai

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Learn to Expect the Unexpected: Probably Approximately Correct Domain Generalization.

Vikas K. Garg, Adam Tauman Kalai, Katrina Ligett, Zhiwei Steven Wu

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Generalization and Representational Limits of Graph Neural Networks.

Vikas K. Garg, Stefanie Jegelka, Tommi S. Jaakkola

Proceedings of the 37th International Conference on Machine Learning, 2020

Predicting deliberative outcomes.

Vikas K. Garg, Tommi S. Jaakkola

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Multiresolution Transformer Networks: Recurrence is Not Essential for Modeling Hierarchical Structure.

Vikas K. Garg, Inderjit S. Dhillon, Hsiang-Fu Yu

CoRR, 2019

Strategic Prediction with Latent Aggregative Games.

Vikas K. Garg, Tommi S. Jaakkola

CoRR, 2019

Generative Models for Graph-Based Protein Design.

John Ingraham, Vikas K. Garg, Regina Barzilay, Tommi S. Jaakkola

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Online Markov Decoding: Lower Bounds and Near-Optimal Approximation Algorithms.

Vikas K. Garg, Tamar Pichkhadze

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Solving graph compression via optimal transport.

Vikas K. Garg, Tommi S. Jaakkola

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Peek Search: Near-Optimal Online Markov Decoding.

Vikas K. Garg, Tamar Pichkhadze

CoRR, 2018

Sparse Multi-Prototype Classification.

Vikas K. Garg, Lin Xiao, Ofer Dekel

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Learning SMaLL Predictors.

Vikas K. Garg, Ofer Dekel, Lin Xiao

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Supervising Unsupervised Learning.

Vikas K. Garg

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Supervising Unsupervised Learning.

Vikas K. Garg, Adam Kalai

CoRR, 2017

Local Aggregative Games.

Vikas K. Garg, Tommi S. Jaakkola

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016

Meta-Unsupervised-Learning: A supervised approach to unsupervised learning.

Vikas K. Garg, Adam Tauman Kalai

CoRR, 2016

Learning Tree Structured Potential Games.

Vikas K. Garg, Tommi S. Jaakkola

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

CRAFT: ClusteR-specific Assorted Feature selecTion.

Vikas K. Garg, Cynthia Rudin, Tommi S. Jaakkola

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015

DEEP-CARVING: Discovering visual attributes by carving deep neural nets.

Sukrit Shankar, Vikas K. Garg, Roberto Cipolla

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

2014

Multiresolution Matrix Factorization.

Risi Kondor, Nedelina Teneva, Vikas K. Garg

Proceedings of the 31th International Conference on Machine Learning, 2014

2013

Novel Biobjective Clustering (BiGC) Based on Cooperative Game Theory.

Vikas K. Garg, Y. Narahari, M. Narasimha Murty

IEEE Trans. Knowl. Data Eng., 2013

Adaptivity to Local Smoothness and Dimension in Kernel Regression.

Samory Kpotufe, Vikas K. Garg

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Link Label Prediction in Signed Social Networks.

Priyanka Agrawal, Vikas K. Garg, Ramasuri Narayanam

Proceedings of the IJCAI 2013, 2013

Multi-regularization for Fuzzy Co-clustering.

Vikas K. Garg, Sneha Chaudhari, Ankur Narang

Proceedings of the Neural Information Processing - 20th International Conference, 2013

Online Optimization with Dynamic Temporal Uncertainty: Incorporating Short Term Predictions for Renewable Integration in Intelligent Energy Systems.

Vikas K. Garg, T. S. Jayram, Balakrishnan Narayanaswamy

Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence, 2013

2012

Prediction based storage management in the smart grid.

Balakrishnan Narayanaswamy, Vikas K. Garg, T. S. Jayram

Proceedings of the IEEE Third International Conference on Smart Grid Communications, 2012

Online optimization for the smart (micro) grid.

Balakrishnan Narayanaswamy, Vikas K. Garg, T. S. Jayram

Proceedings of the 3rd International Conference on Energy-Efficient Computing and Networking, 2012

2011

High throughput data redundancy removal algorithm with scalable performance.

Souvik Bhattacherjee, Ankur Narang, Vikas K. Garg

Proceedings of the High Performance Embedded Architectures and Compilers, 2011

2010

EcoSupply: A Machine Learning Framework for Analyzing the Impact of Ecosystem on Global Supply Chain Dynamics.

Vikas K. Garg, Nukala Viswanadham

Proceedings of the Simulated Evolution and Learning - 8th International Conference, 2010

EPIC: Efficient Integration of Partitional Clustering Algorithms for Classification.

Vikas K. Garg, M. Narasimha Murty

Proceedings of the Simulated Evolution and Learning - 8th International Conference, 2010

Toward Optimal Disk Layout of Genome Scale Suffix Trees.

Vikas K. Garg

Proceedings of the Simulated Evolution and Learning - 8th International Conference, 2010

Highly scalable parallel collaborative filtering algorithm.

Ankur Narang, Raj Gupta, Anupam Joshi, Vikas K. Garg

Proceedings of the 2010 International Conference on High Performance Computing, 2010

Real-time memory efficient data redundancy removal algorithm.

Vikas K. Garg, Ankur Narang, Souvik Bhattacherjee

Proceedings of the 19th ACM Conference on Information and Knowledge Management, 2010

2009

Feature subspace SVMs (FS-SVMs) for high dimensional handwritten digit recognition.

Vikas K. Garg, M. Narasimha Murty

Int. J. Data Min. Model. Manag., 2009

RACK: RApid clustering using K-means algorithm.

Vikas K. Garg, M. Narasimha Murty

Proceedings of the IEEE Conference on Automation Science and Engineering, 2009