Devendra Singh Dhami

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 67

Top Topics

Statistical Relational Learning

Causal Inference

Top Venues

Publications

Daniel Ochs, Karsten Wiertz, Sebastian Bußmann, Kristian Kersting, Devendra Singh Dhami
Effective Risk Detection for Natural Gas Pipelines Using Low-Resolution Satellite Images. Remote. Sens. 16 (2) (2024)
Hikaru Shindo, Manuel Brack, Gopika Sudhakaran, Devendra Singh Dhami, Patrick Schramowski, Kristian Kersting
DeiSAM: Segment Anything with Deictic Prompting. CoRR (2024)
Binon Teji, Swarup Roy, Devendra Singh Dhami, Dinabandhu Bhandari, Pietro Hiram Guzzi
Graph Embedding Techniques for Predicting Missing Links in Biological Networks: An Empirical Evaluation. IEEE Trans. Emerg. Top. Comput. 12 (1) (2024)
Antonia Wüst, Wolfgang Stammer, Quentin Delfosse, Devendra Singh Dhami, Kristian Kersting
Pix2Code: Learning to Compose Neural Visual Concepts as Programs. CoRR (2024)
Maurice Kraus, Felix Divo, David Steinmann, Devendra Singh Dhami, Kristian Kersting
United We Pretrain, Divided We Fail! Representation Learning for Time Series by Pretraining on 75 Datasets at Once. CoRR (2024)
Simon Kohaut, Benedict Flade, Devendra Singh Dhami, Julian Eggert, Kristian Kersting
Mission Design for Unmanned Aerial Vehicles using Hybrid Probabilistic Logic Program. CoRR (2024)
Jingyuan Sha, Hikaru Shindo, Quentin Delfosse, Kristian Kersting, Devendra Singh Dhami
EXPIL: Explanatory Predicate Invention for Learning in Games. CoRR (2024)
Jonas Seng, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting
Learning Large DAGs is Harder than you Think: Many Losses are Minimal for the Wrong DAG. ICLR (2024)
Simon Kohaut, Benedict Flade, Devendra Singh Dhami, Julian Eggert, Kristian Kersting
Towards Probabilistic Clearance, Explanation and Optimization. CoRR (2024)
Matej Zecevic, Devendra Singh Dhami, Kristian Kersting
Structural causal models reveal confounder bias in linear program modelling. Mach. Learn. 113 (3) (2024)
Simon Kohaut, Benedict Flade, Devendra Singh Dhami, Julian Eggert, Kristian Kersting
Mission Design for Unmanned Aerial Vehicles using Hybrid Probabilistic Logic Programs. ITSC (2023)
Moritz Willig, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting
Do Not Marginalize Mechanisms, Rather Consolidate! NeurIPS (2023)
Arseny Skryagin, Daniel Ochs, Devendra Singh Dhami, Kristian Kersting
Scalable Neural-Probabilistic Answer Set Programming. CoRR (2023)
Quentin Delfosse, Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting
Interpretable and Explainable Logical Policies via Neurally Guided Symbolic Abstraction. NeurIPS (2023)
Matej Zecevic, Moritz Willig, Devendra Singh Dhami, Kristian Kersting
Causal Parrots: Large Language Models May Talk Causality But Are Not Causal. CoRR (2023)
Lukas Helff, Wolfgang Stammer, Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting
V-LoL: A Diagnostic Dataset for Visual Logical Learning. CoRR (2023)
Jingyuan Sha, Hikaru Shindo, Kristian Kersting, Devendra Singh Dhami
Neural-Symbolic Predicate Invention: Learning Relational Concepts from Visual Scenes. NeSy (2023)
Hikaru Shindo, Viktor Pfanschilling, Devendra Singh Dhami, Kristian Kersting
Learning Differentiable Logic Programs for Abstract Visual Reasoning. CoRR (2023)
Gopika Sudhakaran, Devendra Singh Dhami, Kristian Kersting, Stefan Roth
Vision Relation Transformer for Unbiased Scene Graph Generation. ICCV (2023)
Quentin Delfosse, Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting
Interpretable and Explainable Logical Policies via Neurally Guided Symbolic Abstraction. CoRR (2023)
Arseny Skryagin, Daniel Ochs, Devendra Singh Dhami, Kristian Kersting
Scalable Neural-Probabilistic Answer Set Programming. J. Artif. Intell. Res. 78 (2023)
Martin Mundt, Keiland W. Cooper, Devendra Singh Dhami, Adèle H. Ribeiro, James Seale Smith, Alexis Bellot, Tyler L. Hayes
Continual Causality: A Retrospective of the Inaugural AAAI-23 Bridge Program. AAAI Bridge Program (2023)
Moritz Willig, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting
Do Not Marginalize Mechanisms, Rather Consolidate! CoRR (2023)
Matej Zecevic, Moritz Willig, Devendra Singh Dhami, Kristian Kersting
Causal Parrots: Large Language Models May Talk Causality But Are Not Causal. Trans. Mach. Learn. Res. 2023 (2023)
Matej Zecevic, Devendra Singh Dhami, Kristian Kersting
Not All Causal Inference is the Same. Trans. Mach. Learn. Res. 2023 (2023)
Hikaru Shindo, Viktor Pfanschilling, Devendra Singh Dhami, Kristian Kersting
αILP: thinking visual scenes as differentiable logic programs. Mach. Learn. 112 (5) (2023)
Gopika Sudhakaran, Devendra Singh Dhami, Kristian Kersting, Stefan Roth
Vision Relation Transformer for Unbiased Scene Graph Generation. CoRR (2023)
Matej Zecevic, Moritz Willig, Devendra Singh Dhami, Kristian Kersting
Pearl Causal Hierarchy on Image Data: Intricacies & Challenges. CoRR (2022)
Arseny Skryagin, Wolfgang Stammer, Daniel Ochs, Devendra Singh Dhami, Kristian Kersting
Neural-Probabilistic Answer Set Programming. KR (2022)
Zhongjie Yu, Fabrizio Ventola, Nils Thoma, Devendra Singh Dhami, Martin Mundt, Kristian Kersting
Predictive Whittle networks for time series. UAI (2022)
Florian Peter Busch, Matej Zecevic, Kristian Kersting, Devendra Singh Dhami
Attributions Beyond Neural Networks: The Linear Program Case. CoRR (2022)
Jonas Seng, Pooja Prasad, Devendra Singh Dhami, Kristian Kersting
HANF: Hyperparameter And Neural Architecture Search in Federated Learning. CoRR (2022)
David Steinmann, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting
Machines Explaining Linear Programs. CoRR (2022)
Björn Deiseroth, Patrick Schramowski, Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting
LogicRank: Logic Induced Reranking for Generative Text-to-Image Systems. CoRR (2022)
Salahedine Youssef, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting
Towards a Solution to Bongard Problems: A Causal Approach. CoRR (2022)
Viktor Pfanschilling, Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting
Sum-Product Loop Programming: From Probabilistic Circuits to Loop Programming. KR (2022)
Matej Zecevic, Florian Peter Busch, Devendra Singh Dhami, Kristian Kersting
Finding Structure and Causality in Linear Programs. CoRR (2022)
Zihan Ye, Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting
Differentiable Meta logical Programming. CoRR (2022)
Moritz Willig, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting
Can Foundation Models Talk Causality? CoRR (2022)
Jonas Seng, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting
Tearing Apart NOTEARS: Controlling the Graph Prediction via Variance Manipulation. CoRR (2022)
Mei Ling Fang, Devendra Singh Dhami, Kristian Kersting
DP-CTGAN: Differentially Private Medical Data Generation Using CTGANs. AIME (2022)
Devendra Singh Dhami, Siwen Yan, Gautam Kunapuli, David Page, Sriraam Natarajan
Predicting Drug-Drug Interactions from Heterogeneous Data: An Embedding Approach. AIME (2021)
Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting
Neuro-Symbolic Forward Reasoning. CoRR (2021)
Moritz Willig, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting
The Causal Loss: Driving Correlation to Imply Causation. CoRR (2021)
Matej Zecevic, Devendra Singh Dhami, Kristian Kersting
Intriguing Parameters of Structural Causal Models. CoRR (2021)
Arseny Skryagin, Wolfgang Stammer, Daniel Ochs, Devendra Singh Dhami, Kristian Kersting
SLASH: Embracing Probabilistic Circuits into Neural Answer Set Programming. CoRR (2021)
Zhongjie Yu, Devendra Singh Dhami, Kristian Kersting
Sum-Product-Attention Networks: Leveraging Self-Attention in Probabilistic Circuits. CoRR (2021)
Mayukh Das, Devendra Singh Dhami, Yang Yu, Gautam Kunapuli, Sriraam Natarajan
Human-Guided Learning of Column Networks: Knowledge Injection for Relational Deep Learning. COMAD/CODS (2021)
Devendra Singh Dhami, Siwen Yan, Sriraam Natarajan
Bridging Graph Neural Networks and Statistical Relational Learning: Relational One-Class GCN. CoRR (2021)
Matej Zecevic, Devendra Singh Dhami, Kristian Kersting
On the Tractability of Neural Causal Inference. CoRR (2021)
Matej Zecevic, Devendra Singh Dhami, Athresh Karanam, Sriraam Natarajan, Kristian Kersting
Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models. NeurIPS (2021)
Devendra Singh Dhami, Siwen Yan, Gautam Kunapuli, David Page, Sriraam Natarajan
Predicting Drug-Drug Interactions from Heterogeneous Data: An Embedding Approach. CoRR (2021)
Matej Zecevic, Devendra Singh Dhami, Petar Velickovic, Kristian Kersting
Relating Graph Neural Networks to Structural Causal Models. CoRR (2021)
Fabrizio Ventola, Devendra Singh Dhami, Kristian Kersting
Generative Clausal Networks: Relational Decision Trees as Probabilistic Circuits. ILP (2021)
Matej Zecevic, Devendra Singh Dhami, Athresh Karanam, Sriraam Natarajan, Kristian Kersting
Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models. CoRR (2021)
Matej Zecevic, Devendra Singh Dhami, Constantin A. Rothkopf, Kristian Kersting
Structural Causal Interpretation Theorem. CoRR (2021)
Devendra Singh Dhami, Siwen Yan, Gautam Kunapuli, Sriraam Natarajan
Non-parametric Learning of Embeddings for Relational Data Using Gaifman Locality Theorem. ILP (2021)
Devendra Singh Dhami, Mayukh Das, Sriraam Natarajan
Beyond Simple Images: Human Knowledge-Guided GANs for Clinical Data Generation. KR (2021)
Devendra Singh Dhami, Siwen Yan, Gautam Kunapuli, Sriraam Natarajan
Non-Parametric Learning of Gaifman Models. CoRR (2020)
Devendra Singh Dhami, Mayukh Das, Sriraam Natarajan
Knowledge Intensive Learning of Generative Adversarial Networks. KiML@KDD (2020)
Siwen Yan, Devendra Singh Dhami, Sriraam Natarajan
The Curious Case of Stacking Boosted Relational Dependency Networks. ICBINB@NeurIPS (2020)
Mayukh Das, Devendra Singh Dhami, Gautam Kunapuli, Kristian Kersting, Sriraam Natarajan
Fast Relational Probabilistic Inference and Learning: Approximate Counting via Hypergraphs. AAAI (2019)
Mayukh Das, Devendra Singh Dhami, Yang Yu, Gautam Kunapuli, Sriraam Natarajan
Knowledge-augmented Column Networks: Guiding Deep Learning with Advice. CoRR (2019)
Mayukh Das, Yang Yu, Devendra Singh Dhami, Gautam Kunapuli, Sriraam Natarajan
Human-Guided Learning of Column Networks: Augmenting Deep Learning with Advice. CoRR (2019)
Devendra Singh Dhami, Gautam Kunapuli, David Page, Sriraam Natarajan
Predicting Drug-Drug Interactions from Molecular Structure Images. CoRR (2019)
Devendra Singh Dhami, Ameet Soni, David Page, Sriraam Natarajan
Identifying Parkinson's Patients: A Functional Gradient Boosting Approach. AIME (2017)
Devendra Singh Dhami, David Leake, Sriraam Natarajan
Knowledge-Based Morphological Classification of Galaxies from Vision Features. AAAI Workshops (2017)