Greg Ver Steeg

ORCID

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 131

Top Venues

Publications

Alessandro Achille, Greg Ver Steeg, Tian Yu Liu, Matthew Trager, Carson Klingenberg, Stefano Soatto
Interpretable Measures of Conceptual Similarity by Complexity-Constrained Descriptive Auto-Encoding. CoRR (2024)
Qiang Li, Greg Ver Steeg, Jesus Malo
Functional connectivity via total correlation: Analytical results in visual areas. Neurocomputing 571 (2024)
Myrl G. Marmarelis, Fred Morstatter, Aram Galstyan, Greg Ver Steeg
Policy Learning for Localized Interventions from Observational Data. AISTATS (2024)
Xianghao Kong, Ollie Liu, Han Li, Dani Yogatama, Greg Ver Steeg
Interpretable Diffusion via Information Decomposition. ICLR (2024)
Haz Sameen Shahgir, Xianghao Kong, Greg Ver Steeg, Yue Dong
Asymmetric Bias in Text-to-Image Generation with Adversarial Attacks. ACL (Findings) (2024)
Yao Qiang, Subhrangshu Nandi, Ninareh Mehrabi, Greg Ver Steeg, Anoop Kumar, Anna Rumshisky, Aram Galstyan
Prompt Perturbation Consistency Learning for Robust Language Models. EACL (Findings) (2024)
Yao Qiang, Subhrangshu Nandi, Ninareh Mehrabi, Greg Ver Steeg, Anoop Kumar, Anna Rumshisky, Aram Galstyan
Prompt Perturbation Consistency Learning for Robust Language Models. CoRR (2024)
Myrl G. Marmarelis, Greg Ver Steeg, Aram Galstyan, Fred Morstatter
Ensembled Prediction Intervals for Causal Outcomes Under Hidden Confounding. CLeaR (2024)
Yunshu Wu, Yingtao Luo, Xianghao Kong, Evangelos E. Papalexakis, Greg Ver Steeg
Your Diffusion Model is Secretly a Noise Classifier and Benefits from Contrastive Training. CoRR (2024)
Neal Lawton, Anoop Kumar, Govind Thattai, Aram Galstyan, Greg Ver Steeg
Neural Architecture Search for Parameter-Efficient Fine-tuning of Large Pre-trained Language Models. CoRR (2023)
Umang Gupta, Aram Galstyan, Greg Ver Steeg
Jointly Reparametrized Multi-Layer Adaptation for Efficient and Private Tuning. CoRR (2023)
Myrl G. Marmarelis, Elizabeth Haddad, Andrew Jesson, Neda Jahanshad, Aram Galstyan, Greg Ver Steeg
Partial identification of dose responses with hidden confounders. UAI (2023)
Umang Gupta, Aram Galstyan, Greg Ver Steeg
Jointly Reparametrized Multi-Layer Adaptation for Efficient and Private Tuning. ACL (Findings) (2023)
Rob Brekelmans, Sicong Huang, Marzyeh Ghassemi, Greg Ver Steeg, Roger B. Grosse, Alireza Makhzani
Improving Mutual Information Estimation with Annealed and Energy-Based Bounds. CoRR (2023)
Xianghao Kong, Ollie Liu, Han Li, Dani Yogatama, Greg Ver Steeg
Interpretable Diffusion via Information Decomposition. CoRR (2023)
Elizabeth Haddad, Myrl G. Marmarelis, Talia M. Nir, Aram Galstyan, Greg Ver Steeg, Neda Jahanshad
Causal Sensitivity Analysis for Hidden Confounding: Modeling the Sex-Specific Role of Diet on the Aging Brain. MLCN@MICCAI (2023)
Umang Gupta, Tamoghna Chattopadhyay, Nikhil J. Dhinagar, Paul M. Thompson, Greg Ver Steeg
Transferring Models Trained on Natural Images to 3D MRI via Position Encoded Slice Models. ISBI (2023)
Neal Lawton, Anoop Kumar, Govind Thattai, Aram Galstyan, Greg Ver Steeg
Neural Architecture Search for Parameter-Efficient Fine-tuning of Large Pre-trained Language Models. ACL (Findings) (2023)
Elan Markowitz, Ziyan Jiang, Fan Yang, Xing Fan, Tony Chen, Greg Ver Steeg, Aram Galstyan
Multi-Task Knowledge Enhancement for Zero-Shot and Multi-Domain Recommendation in an AI Assistant Application. CoRR (2023)
Myrl G. Marmarelis, Greg Ver Steeg, Aram Galstyan, Fred Morstatter
Tighter Prediction Intervals for Causal Outcomes Under Hidden Confounding. CoRR (2023)
Xianghao Kong, Rob Brekelmans, Greg Ver Steeg
Information-Theoretic Diffusion. ICLR (2023)
Arghya Datta, Subhrangshu Nandi, Jingcheng Xu, Greg Ver Steeg, He Xie, Anoop Kumar, Aram Galstyan
Measuring and Mitigating Local Instability in Deep Neural Networks. CoRR (2023)
Arghya Datta, Subhrangshu Nandi, Jingcheng Xu, Greg Ver Steeg, He Xie, Anoop Kumar, Aram Galstyan
Measuring and Mitigating Local Instability in Deep Neural Networks. ACL (Findings) (2023)
Umang Gupta, Tamoghna Chattopadhyay, Nikhil Dhinagar, Paul M. Thompson, Greg Ver Steeg, Alzheimer's Disease Neuroimaging Initiative
Transferring Models Trained on Natural Images to 3D MRI via Position Encoded Slice Models. CoRR (2023)
Haz Sameen Shahgir, Xianghao Kong, Greg Ver Steeg, Yue Dong
Asymmetric Bias in Text-to-Image Generation with Adversarial Attacks. CoRR (2023)
Dheeraj Komandur, Umang Gupta, Tamoghna Chattopadhyay, Nikhil J. Dhinagar, Sophia I. Thomopoulos, Jiu-Chiuan Chen, Dan Beavers, Greg Ver Steeg, Paul M. Thompson
Unsupervised harmonization of brain MRI using 3D CycleGANs and its effect on brain age prediction. SIPAIM (2023)
Xianghao Kong, Rob Brekelmans, Greg Ver Steeg
Information-Theoretic Diffusion. CoRR (2023)
Myrl G. Marmarelis, Greg Ver Steeg, Aram Galstyan
A Metric Space for Point Process Excitations. J. Artif. Intell. Res. 73 (2022)
Umang Gupta, Jwala Dhamala, Varun Kumar, Apurv Verma, Yada Pruksachatkun, Satyapriya Krishna, Rahul Gupta, Kai-Wei Chang, Greg Ver Steeg, Aram Galstyan
Mitigating Gender Bias in Distilled Language Models via Counterfactual Role Reversal. ACL (Findings) (2022)
Hrayr Harutyunyan, Greg Ver Steeg, Aram Galstyan
Formal limitations of sample-wise information-theoretic generalization bounds. ITW (2022)
Dimitris Stripelis, Umang Gupta, Nikhil Dhinagar, Greg Ver Steeg, Paul M. Thompson, José Luis Ambite
Towards Sparsified Federated Neuroimaging Models via Weight Pruning. CoRR (2022)
Qiang Li, Greg Ver Steeg, Shujian Yu, Jesus Malo
Functional Connectome of the Human Brain with Total Correlation. Entropy 24 (12) (2022)
Myrl G. Marmarelis, Greg Ver Steeg, Aram Galstyan
Bounding the Effects of Continuous Treatments for Hidden Confounders. CoRR (2022)
Dimitris Stripelis, Umang Gupta, Hamza Saleem, Nikhil Dhinagar, Tanmay Ghai, Rafael Sanchez, Chrysovalantis Anastasiou, Armaghan Asghar, Greg Ver Steeg, Srivatsan Ravi, Muhammad Naveed, Paul M. Thompson, José Luis Ambite
Secure Federated Learning for Neuroimaging. CoRR (2022)
Rob Brekelmans, Sicong Huang, Marzyeh Ghassemi, Greg Ver Steeg, Roger Baker Grosse, Alireza Makhzani
Improving Mutual Information Estimation with Annealed and Energy-Based Bounds. ICLR (2022)
Tigran Galstyan, Hrayr Harutyunyan, Hrant Khachatrian, Greg Ver Steeg, Aram Galstyan
Failure Modes of Domain Generalization Algorithms. CVPR (2022)
Umang Gupta, Jwala Dhamala, Varun Kumar, Apurv Verma, Yada Pruksachatkun, Satyapriya Krishna, Rahul Gupta, Kai-Wei Chang, Greg Ver Steeg, Aram Galstyan
Mitigating Gender Bias in Distilled Language Models via Counterfactual Role Reversal. CoRR (2022)
Dimitris Stripelis, Umang Gupta, Nikhil Dhinagar, Greg Ver Steeg, Paul M. Thompson, José Luis Ambite
Towards Sparsified Federated Neuroimaging Models via Weight Pruning. DeCaF/FAIR@MICCAI (2022)
Marcin Abram, Keith Burghardt, Greg Ver Steeg, Aram Galstyan, Rémi Dingreville
Inferring topological transitions in pattern-forming processes with self-supervised learning. CoRR (2022)
Dimitris Stripelis, Umang Gupta, Greg Ver Steeg, José Luis Ambite
Federated Progressive Sparsification (Purge, Merge, Tune)+. CoRR (2022)
Hrayr Harutyunyan, Greg Ver Steeg, Aram Galstyan
Formal limitations of sample-wise information-theoretic generalization bounds. CoRR (2022)
Elan Markowitz, Keshav Balasubramanian, Mehrnoosh Mirtaheri, Murali Annavaram, Aram Galstyan, Greg Ver Steeg
StATIK: Structure and Text for Inductive Knowledge Graph Completion. NAACL-HLT (Findings) (2022)
Judith Gaspers, Anoop Kumar, Greg Ver Steeg, Aram Galstyan
Temporal Generalization for Spoken Language Understanding. NAACL-HLT (Industry Papers) (2022)
Elan Sopher Markowitz, Keshav Balasubramanian, Mehrnoosh Mirtaheri, Sami Abu-El-Haija, Bryan Perozzi, Greg Ver Steeg, Aram Galstyan
Graph Traversal with Tensor Functionals: A Meta-Algorithm for Scalable Learning. ICLR (2021)
Elan Markowitz, Keshav Balasubramanian, Mehrnoosh Mirtaheri, Sami Abu-El-Haija, Bryan Perozzi, Greg Ver Steeg, Aram Galstyan
Graph Traversal with Tensor Functionals: A Meta-Algorithm for Scalable Learning. CoRR (2021)
Sami Abu-El-Haija, Valentino Crespi, Greg Ver Steeg, Aram Galstyan
Fast Graph Learning with Unique Optimal Solutions. CoRR (2021)
Ninareh Mehrabi, Umang Gupta, Fred Morstatter, Greg Ver Steeg, Aram Galstyan
Attributing Fair Decisions with Attention Interventions. CoRR (2021)
Umang Gupta, Aaron M. Ferber, Bistra Dilkina, Greg Ver Steeg
Controllable Guarantees for Fair Outcomes via Contrastive Information Estimation. CoRR (2021)
Kyle Reing, Greg Ver Steeg, Aram Galstyan
Influence Decompositions For Neural Network Attribution. AISTATS (2021)
Umang Gupta, Pradeep K. Lam, Greg Ver Steeg, Paul M. Thompson
Improved Brain Age Estimation With Slice-Based Set Networks. ISBI (2021)
Kyle Reing, Greg Ver Steeg, Aram Galstyan
Discovering Higher-Order Interactions Through Neural Information Decomposition. Entropy 23 (1) (2021)
James O'Neill, Greg Ver Steeg, Aram Galstyan
Layer-Wise Neural Network Compression via Layer Fusion. ACML (2021)
Hrayr Harutyunyan, Maxim Raginsky, Greg Ver Steeg, Aram Galstyan
Information-theoretic generalization bounds for black-box learning algorithms. CoRR (2021)
Dimitris Stripelis, Hamza Saleem, Tanmay Ghai, Nikhil Dhinagar, Umang Gupta, Chrysovalantis Anastasiou, Greg Ver Steeg, Srivatsan Ravi, Muhammad Naveed, Paul M. Thompson, José Luis Ambite
Secure Neuroimaging Analysis using Federated Learning with Homomorphic Encryption. CoRR (2021)
Sami Abu-El-Haija, Hesham Mostafa, Marcel Nassar, Valentino Crespi, Greg Ver Steeg, Aram Galstyan
Implicit SVD for Graph Representation Learning. NeurIPS (2021)
Umang Gupta, Pradeep Lam, Greg Ver Steeg, Paul Thompson
Improved Brain Age Estimation with Slice-based Set Networks. CoRR (2021)
Mehrnoosh Mirtaheri, Sami Abu-El-Haija, Fred Morstatter, Greg Ver Steeg, Aram Galstyan
Identifying and Analyzing Cryptocurrency Manipulations in Social Media. IEEE Trans. Comput. Soc. Syst. 8 (3) (2021)
Sami Abu-El-Haija, Hesham Mostafa, Marcel Nassar, Valentino Crespi, Greg Ver Steeg, Aram Galstyan
Implicit SVD for Graph Representation Learning. CoRR (2021)
Vaden Masrani, Rob Brekelmans, Thang Bui, Frank Nielsen, Aram Galstyan, Greg Ver Steeg, Frank Wood
q-Paths: Generalizing the Geometric Annealing Path using Power Means. CoRR (2021)
Vaden Masrani, Rob Brekelmans, Thang Bui, Frank Nielsen, Aram Galstyan, Greg Ver Steeg, Frank Wood
q-Paths: Generalizing the geometric annealing path using power means. UAI (2021)
Umang Gupta, Dimitris Stripelis, Pradeep K. Lam, Paul M. Thompson, José Luis Ambite, Greg Ver Steeg
Membership Inference Attacks on Deep Regression Models for Neuroimaging. CoRR (2021)
Umang Gupta, Dimitris Stripelis, Pradeep K. Lam, Paul M. Thompson, José Luis Ambite, Greg Ver Steeg
Membership Inference Attacks on Deep Regression Models for Neuroimaging. MIDL (2021)
Tigran Galstyan, Hrayr Harutyunyan, Hrant Khachatrian, Greg Ver Steeg, Aram Galstyan
Failure Modes of Domain Generalization Algorithms. CoRR (2021)
Greg Ver Steeg, Aram Galstyan
Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling. NeurIPS (2021)
Hrayr Harutyunyan, Maxim Raginsky, Greg Ver Steeg, Aram Galstyan
Information-theoretic generalization bounds for black-box learning algorithms. NeurIPS (2021)
Umang Gupta, Aaron M. Ferber, Bistra Dilkina, Greg Ver Steeg
Controllable Guarantees for Fair Outcomes via Contrastive Information Estimation. AAAI (2021)
Greg Ver Steeg, Aram Galstyan
Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling. CoRR (2021)
Rob Brekelmans, Vaden Masrani, Thang Bui, Frank Wood, Aram Galstyan, Greg Ver Steeg, Frank Nielsen
Annealed Importance Sampling with q-Paths. CoRR (2020)
Daniel Moyer, Greg Ver Steeg, Paul M. Thompson
Overview of Scanner Invariant Representations. CoRR (2020)
Ayush Jaiswal, Daniel Moyer, Greg Ver Steeg, Wael AbdAlmageed, Premkumar Natarajan
Invariant Representations through Adversarial Forgetting. AAAI (2020)
Hrayr Harutyunyan, Kyle Reing, Greg Ver Steeg, Aram Galstyan
Improving generalization by controlling label-noise information in neural network weights. ICML (2020)
Sahil Garg, Irina Rish, Guillermo A. Cecchi, Palash Goyal, Sarik Ghazarian, Shuyang Gao, Greg Ver Steeg, Aram Galstyan
Modeling Dialogues with Hashcode Representations: A Nonparametric Approach. AAAI (2020)
Rob Brekelmans, Frank Nielsen, Alireza Makhzani, Aram Galstyan, Greg Ver Steeg
Likelihood Ratio Exponential Families. CoRR (2020)
Myrl G. Marmarelis, Greg Ver Steeg, Aram Galstyan
Event Cartography: Latent Point Process Embeddings. CoRR (2020)
James O'Neill, Greg Ver Steeg, Aram Galstyan
Compressing Deep Neural Networks via Layer Fusion. CoRR (2020)
Tigran Galstyan, Hrant Khachatrian, Greg Ver Steeg, Aram Galstyan
Robust Classification under Class-Dependent Domain Shift. CoRR (2020)
Rob Brekelmans, Vaden Masrani, Frank Wood, Greg Ver Steeg, Aram Galstyan
All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference. CoRR (2020)
Rob Brekelmans, Vaden Masrani, Frank Wood, Greg Ver Steeg, Aram Galstyan
All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference. ICML (2020)
Hrayr Harutyunyan, Kyle Reing, Greg Ver Steeg, Aram Galstyan
Improving Generalization by Controlling Label-Noise Information in Neural Network Weights. CoRR (2020)
Kyle Reing, Greg Ver Steeg, Aram Galstyan
Maximizing Multivariate Information With Error-Correcting Codes. IEEE Trans. Inf. Theory 66 (5) (2020)
Mehrnoosh Mirtaheri, Sami Abu-El-Haija, Fred Morstatter, Greg Ver Steeg, Aram Galstyan
Identifying and Analyzing Cryptocurrency Manipulations in Social Media. CoRR (2019)
Hrayr Harutyunyan, Daniel Moyer, Hrant Khachatrian, Greg Ver Steeg, Aram Galstyan
Efficient Covariance Estimation from Temporal Data. CoRR (2019)
Sahil Garg, Aram Galstyan, Greg Ver Steeg, Irina Rish, Guillermo A. Cecchi, Shuyang Gao
Kernelized Hashcode Representations for Relation Extraction. AAAI (2019)
Sahil Garg, Aram Galstyan, Greg Ver Steeg, Guillermo A. Cecchi
Nearly-Unsupervised Hashcode Representations for Biomedical Relation Extraction. EMNLP/IJCNLP (1) (2019)
Ayush Jaiswal, Daniel Moyer, Greg Ver Steeg, Wael AbdAlmageed, Premkumar Natarajan
Invariant Representations through Adversarial Forgetting. CoRR (2019)
Rob Brekelmans, Daniel Moyer, Aram Galstyan, Greg Ver Steeg
Exact Rate-Distortion in Autoencoders via Echo Noise. CoRR (2019)
Shuyang Gao, Rob Brekelmans, Greg Ver Steeg, Aram Galstyan
Auto-Encoding Total Correlation Explanation. AISTATS (2019)
Sami Abu-El-Haija, Bryan Perozzi, Amol Kapoor, Nazanin Alipourfard, Kristina Lerman, Hrayr Harutyunyan, Greg Ver Steeg, Aram Galstyan
MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing. ICML (2019)
Rob Brekelmans, Daniel Moyer, Aram Galstyan, Greg Ver Steeg
Exact Rate-Distortion in Autoencoders via Echo Noise. NeurIPS (2019)
Sahil Garg, Aram Galstyan, Greg Ver Steeg, Guillermo A. Cecchi
Nearly-Unsupervised Hashcode Representations for Relation Extraction. CoRR (2019)
Greg Ver Steeg, Hrayr Harutyunyan, Daniel Moyer, Aram Galstyan
Fast structure learning with modular regularization. NeurIPS (2019)
Sami Abu-El-Haija, Bryan Perozzi, Amol Kapoor, Hrayr Harutyunyan, Nazanin Alipourfard, Kristina Lerman, Greg Ver Steeg, Aram Galstyan
MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing. CoRR (2019)
Daniel Moyer, Greg Ver Steeg, Chantal M. W. Tax, Paul M. Thompson
Scanner Invariant Representations for Diffusion MRI Harmonization. CoRR (2019)
Ayush Jaiswal, Rob Brekelmans, Daniel Moyer, Greg Ver Steeg, Wael AbdAlmageed, Premkumar Natarajan
Discovery and Separation of Features for Invariant Representation Learning. CoRR (2019)
Daniel Moyer, Shuyang Gao, Rob Brekelmans, Aram Galstyan, Greg Ver Steeg
Invariant Representations without Adversarial Training. NeurIPS (2018)
Sahil Garg, Guillermo A. Cecchi, Irina Rish, Shuyang Gao, Greg Ver Steeg, Sarik Ghazarian, Palash Goyal, Aram Galstyan
Dialogue Modeling Via Hash Functions. LaCATODA@IJCAI (2018)
Neal Lawton, Aram Galstyan, Greg Ver Steeg
A Forest Mixture Bound for Block-Free Parallel Inference. CoRR (2018)
Sahil Garg, Greg Ver Steeg, Aram Galstyan
Stochastic Learning of Nonstationary Kernels for Natural Language Modeling. CoRR (2018)
Kyle Reing, Greg Ver Steeg, Aram Galstyan
Maximizing Multivariate Information with Error-Correcting Codes. CoRR (2018)
Daniel Moyer, Paul M. Thompson, Greg Ver Steeg
Measures of Tractography Convergence. CoRR (2018)

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Publication Activity (10 Years)

Top Topics

Top Venues

Greg Ver Steeg