Devendra Singh Dhami

According to our database, Devendra Singh Dhami authored at least 55 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Effective Risk Detection for Natural Gas Pipelines Using Low-Resolution Satellite Images.

Daniel Ochs, Karsten Wiertz, Sebastian Bußmann, Kristian Kersting, Devendra Singh Dhami

Remote. Sens., January, 2024

Graph Embedding Techniques for Predicting Missing Links in Biological Networks: An Empirical Evaluation.

Binon Teji, Swarup Roy, Devendra Singh Dhami, Dinabandhu Bhandari, Pietro Hiram Guzzi

IEEE Trans. Emerg. Top. Comput., 2024

Structural causal models reveal confounder bias in linear program modelling.

Matej Zecevic, Devendra Singh Dhami, Kristian Kersting

Mach. Learn., 2024

United We Pretrain, Divided We Fail! Representation Learning for Time Series by Pretraining on 75 Datasets at Once.

Maurice Kraus, Felix Divo, David Steinmann, Devendra Singh Dhami, Kristian Kersting

CoRR, 2024

DeiSAM: Segment Anything with Deictic Prompting.

Hikaru Shindo, Manuel Brack, Gopika Sudhakaran, Devendra Singh Dhami, Patrick Schramowski, Kristian Kersting

CoRR, 2024

Pix2Code: Learning to Compose Neural Visual Concepts as Programs.

Antonia Wüst, Wolfgang Stammer, Quentin Delfosse, Devendra Singh Dhami, Kristian Kersting

CoRR, 2024

2023

αILP: thinking visual scenes as differentiable logic programs.

Hikaru Shindo, Viktor Pfanschilling, Devendra Singh Dhami, Kristian Kersting

Mach. Learn., May, 2023

Scalable Neural-Probabilistic Answer Set Programming.

Arseny Skryagin, Daniel Ochs, Devendra Singh Dhami, Kristian Kersting

J. Artif. Intell. Res., 2023

Causal Parrots: Large Language Models May Talk Causality But Are Not Causal.

Matej Zecevic, Moritz Willig, Devendra Singh Dhami, Kristian Kersting

CoRR, 2023

Learning Differentiable Logic Programs for Abstract Visual Reasoning.

Hikaru Shindo, Viktor Pfanschilling, Devendra Singh Dhami, Kristian Kersting

CoRR, 2023

V-LoL: A Diagnostic Dataset for Visual Logical Learning.

Lukas Helff, Wolfgang Stammer, Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting

CoRR, 2023

Do Not Marginalize Mechanisms, Rather Consolidate!

Moritz Willig, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting

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

Interpretable and Explainable Logical Policies via Neurally Guided Symbolic Abstraction.

Quentin Delfosse, Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting

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

Neural-Symbolic Predicate Invention: Learning Relational Concepts from Visual Scenes.

Jingyuan Sha, Hikaru Shindo, Kristian Kersting, Devendra Singh Dhami

Proceedings of the 17th International Workshop on Neural-Symbolic Learning and Reasoning, 2023

Mission Design for Unmanned Aerial Vehicles using Hybrid Probabilistic Logic Programs.

Simon Kohaut, Benedict Flade, Devendra Singh Dhami, Julian Eggert, Kristian Kersting

Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2023

Vision Relation Transformer for Unbiased Scene Graph Generation.

Gopika Sudhakaran, Devendra Singh Dhami, Kristian Kersting, Stefan Roth

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Continual Causality: A Retrospective of the Inaugural AAAI-23 Bridge Program.

Martin Mundt, Keiland W. Cooper, Devendra Singh Dhami, Adèle H. Ribeiro, James Seale Smith, Alexis Bellot, Tyler L. Hayes

Proceedings of the AAAI Bridge Program on Continual Causality, 2023

2022

Pearl Causal Hierarchy on Image Data: Intricacies & Challenges.

Matej Zecevic, Moritz Willig, Devendra Singh Dhami, Kristian Kersting

CoRR, 2022

Differentiable Meta logical Programming.

Zihan Ye, Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting

CoRR, 2022

LogicRank: Logic Induced Reranking for Generative Text-to-Image Systems.

Björn Deiseroth, Patrick Schramowski, Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting

CoRR, 2022

HANF: Hyperparameter And Neural Architecture Search in Federated Learning.

Jonas Seng, Pooja Prasad, Devendra Singh Dhami, Kristian Kersting

CoRR, 2022

Can Foundation Models Talk Causality?

Moritz Willig, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting

CoRR, 2022

Attributions Beyond Neural Networks: The Linear Program Case.

Florian Peter Busch, Matej Zecevic, Kristian Kersting, Devendra Singh Dhami

CoRR, 2022

Towards a Solution to Bongard Problems: A Causal Approach.

Salahedine Youssef, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting

CoRR, 2022

Tearing Apart NOTEARS: Controlling the Graph Prediction via Variance Manipulation.

Jonas Seng, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting

CoRR, 2022

Machines Explaining Linear Programs.

David Steinmann, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting

CoRR, 2022

Finding Structure and Causality in Linear Programs.

Matej Zecevic, Florian Peter Busch, Devendra Singh Dhami, Kristian Kersting

CoRR, 2022

Predictive Whittle networks for time series.

Zhongjie Yu, Fabrizio Ventola, Nils Thoma, Devendra Singh Dhami, Martin Mundt, Kristian Kersting

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Neural-Probabilistic Answer Set Programming.

Arseny Skryagin, Wolfgang Stammer, Daniel Ochs, Devendra Singh Dhami, Kristian Kersting

Proceedings of the 19th International Conference on Principles of Knowledge Representation and Reasoning, 2022

Sum-Product Loop Programming: From Probabilistic Circuits to Loop Programming.

Viktor Pfanschilling, Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting

Proceedings of the 19th International Conference on Principles of Knowledge Representation and Reasoning, 2022

DP-CTGAN: Differentially Private Medical Data Generation Using CTGANs.

Mei Ling Fang, Devendra Singh Dhami, Kristian Kersting

Proceedings of the Artificial Intelligence in Medicine, 2022

2021

The Causal Loss: Driving Correlation to Imply Causation.

Moritz Willig, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting

CoRR, 2021

On the Tractability of Neural Causal Inference.

Matej Zecevic, Devendra Singh Dhami, Kristian Kersting

CoRR, 2021

Neuro-Symbolic Forward Reasoning.

Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting

CoRR, 2021

SLASH: Embracing Probabilistic Circuits into Neural Answer Set Programming.

Arseny Skryagin, Wolfgang Stammer, Daniel Ochs, Devendra Singh Dhami, Kristian Kersting

CoRR, 2021

Structural Causal Interpretation Theorem.

Matej Zecevic, Devendra Singh Dhami, Constantin A. Rothkopf, Kristian Kersting

CoRR, 2021

Sum-Product-Attention Networks: Leveraging Self-Attention in Probabilistic Circuits.

Zhongjie Yu, Devendra Singh Dhami, Kristian Kersting

CoRR, 2021

Relating Graph Neural Networks to Structural Causal Models.

Matej Zecevic, Devendra Singh Dhami, Petar Velickovic, Kristian Kersting

CoRR, 2021

Intriguing Parameters of Structural Causal Models.

Matej Zecevic, Devendra Singh Dhami, Kristian Kersting

CoRR, 2021

Bridging Graph Neural Networks and Statistical Relational Learning: Relational One-Class GCN.

Devendra Singh Dhami, Siwen Yan, Sriraam Natarajan

CoRR, 2021

Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models.

Matej Zecevic, Devendra Singh Dhami, Athresh Karanam, Sriraam Natarajan, Kristian Kersting

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Beyond Simple Images: Human Knowledge-Guided GANs for Clinical Data Generation.

Devendra Singh Dhami, Mayukh Das, Sriraam Natarajan

Proceedings of the 18th International Conference on Principles of Knowledge Representation and Reasoning, 2021

Generative Clausal Networks: Relational Decision Trees as Probabilistic Circuits.

Fabrizio Ventola, Devendra Singh Dhami, Kristian Kersting

Proceedings of the Inductive Logic Programming - 30th International Conference, 2021

Non-parametric Learning of Embeddings for Relational Data Using Gaifman Locality Theorem.

Devendra Singh Dhami, Siwen Yan, Gautam Kunapuli, Sriraam Natarajan

Proceedings of the Inductive Logic Programming - 30th International Conference, 2021

Human-Guided Learning of Column Networks: Knowledge Injection for Relational Deep Learning.

Mayukh Das, Devendra Singh Dhami, Yang Yu, Gautam Kunapuli, Sriraam Natarajan

Proceedings of the CODS-COMAD 2021: 8th ACM IKDD CODS and 26th COMAD, 2021

Predicting Drug-Drug Interactions from Heterogeneous Data: An Embedding Approach.

Devendra Singh Dhami, Siwen Yan, Gautam Kunapuli, David Page, Sriraam Natarajan

Proceedings of the Artificial Intelligence in Medicine, 2021

2020

Non-Parametric Learning of Gaifman Models.

Devendra Singh Dhami, Siwen Yan, Gautam Kunapuli, Sriraam Natarajan

CoRR, 2020

Knowledge Intensive Learning of Generative Adversarial Networks.

Devendra Singh Dhami, Mayukh Das, Sriraam Natarajan

Proceedings of the ACM SIGKDD Workshop on Knowledge-infused Mining and Learning for Social Impact co-located with 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (Virtual) (SIGKDD 2020), 2020

The Curious Case of Stacking Boosted Relational Dependency Networks.

Siwen Yan, Devendra Singh Dhami, Sriraam Natarajan

Proceedings of the "I Can't Believe It's Not Better!" at NeurIPS Workshops, 2020

2019

Predicting Drug-Drug Interactions from Molecular Structure Images.

Devendra Singh Dhami, Gautam Kunapuli, David Page, Sriraam Natarajan

CoRR, 2019

Knowledge-augmented Column Networks: Guiding Deep Learning with Advice.

Mayukh Das, Devendra Singh Dhami, Yang Yu, Gautam Kunapuli, Sriraam Natarajan

CoRR, 2019

Human-Guided Learning of Column Networks: Augmenting Deep Learning with Advice.

Mayukh Das, Yang Yu, Devendra Singh Dhami, Gautam Kunapuli, Sriraam Natarajan

CoRR, 2019

Fast Relational Probabilistic Inference and Learning: Approximate Counting via Hypergraphs.

Mayukh Das, Devendra Singh Dhami, Gautam Kunapuli, Kristian Kersting, Sriraam Natarajan

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2017

Identifying Parkinson's Patients: A Functional Gradient Boosting Approach.

Devendra Singh Dhami, Ameet Soni, David Page, Sriraam Natarajan

Proceedings of the Artificial Intelligence in Medicine, 2017

Knowledge-Based Morphological Classification of Galaxies from Vision Features.

Devendra Singh Dhami, David Leake, Sriraam Natarajan

Proceedings of the Workshops of the The Thirty-First AAAI Conference on Artificial Intelligence, 2017