Knowledge-Based Morphological Classification of Galaxies from Vision Features. - Devendra Singh Dhami; David Leake; Sriraam Natarajan (AAAI Workshops, 2017)

Identifying Parkinson's Patients: A Functional Gradient Boosting Approach. - Devendra Singh Dhami; Ameet Soni; David Page; Sriraam Natarajan (AIME, 2017)

Fast Relational Probabilistic Inference and Learning: Approximate Counting via Hypergraphs. - Mayukh Das; Devendra Singh Dhami; Gautam Kunapuli; Kristian Kersting; Sriraam Natarajan (AAAI, 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)

Knowledge-augmented Column Networks: Guiding Deep Learning with Advice. - Mayukh Das; Devendra Singh Dhami; Yang Yu; Gautam Kunapuli; Sriraam Natarajan (CoRR, 2019)

Predicting Drug-Drug Interactions from Molecular Structure Images. - Devendra Singh Dhami; Gautam Kunapuli; David Page; Sriraam Natarajan (CoRR, 2019)

The Curious Case of Stacking Boosted Relational Dependency Networks. - Siwen Yan; Devendra Singh Dhami; Sriraam Natarajan (ICBINB@NeurIPS, 2020)

Knowledge Intensive Learning of Generative Adversarial Networks. - Devendra Singh Dhami; Mayukh Das; Sriraam Natarajan (KiML@KDD, 2020)

Non-Parametric Learning of Gaifman Models. - Devendra Singh Dhami; Siwen Yan; Gautam Kunapuli; Sriraam Natarajan (CoRR, 2020)

Predicting Drug-Drug Interactions from Heterogeneous Data: An Embedding Approach. - Devendra Singh Dhami; Siwen Yan; Gautam Kunapuli; David Page; Sriraam Natarajan (AIME, 2021)

Human-Guided Learning of Column Networks: Knowledge Injection for Relational Deep Learning. - Mayukh Das; Devendra Singh Dhami; Yang Yu; Gautam Kunapuli; Sriraam Natarajan (COMAD/CODS, 2021)

Non-parametric Learning of Embeddings for Relational Data Using Gaifman Locality Theorem. - Devendra Singh Dhami; Siwen Yan; Gautam Kunapuli; Sriraam Natarajan (ILP, 2021)

Generative Clausal Networks: Relational Decision Trees as Probabilistic Circuits. - Fabrizio Ventola; Devendra Singh Dhami; Kristian Kersting (ILP, 2021)

Beyond Simple Images: Human Knowledge-Guided GANs for Clinical Data Generation. - Devendra Singh Dhami; Mayukh Das; Sriraam Natarajan (KR, 2021)

Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models. - Matej Zecevic; Devendra Singh Dhami; Athresh Karanam; Sriraam Natarajan; Kristian Kersting (NeurIPS, 2021)

Bridging Graph Neural Networks and Statistical Relational Learning: Relational One-Class GCN. - Devendra Singh Dhami; Siwen Yan; Sriraam Natarajan (CoRR, 2021)

Intriguing Parameters of Structural Causal Models. - Matej Zecevic; 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)

Sum-Product-Attention Networks: Leveraging Self-Attention in Probabilistic Circuits. - Zhongjie Yu 001; Devendra Singh Dhami; Kristian Kersting (CoRR, 2021)

Structural Causal Interpretation Theorem. - Matej Zecevic; Devendra Singh Dhami; Constantin A. Rothkopf; 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)

Neuro-Symbolic Forward Reasoning. - Hikaru Shindo; Devendra Singh Dhami; Kristian Kersting (CoRR, 2021)

On the Tractability of Neural Causal Inference. - Matej Zecevic; Devendra Singh Dhami; Kristian Kersting (CoRR, 2021)

The Causal Loss: Driving Correlation to Imply Causation. - Moritz Willig; Matej Zecevic; Devendra Singh Dhami; Kristian Kersting (CoRR, 2021)

DP-CTGAN: Differentially Private Medical Data Generation Using CTGANs. - Mei Ling Fang; Devendra Singh Dhami; Kristian Kersting (AIME, 2022)

Sum-Product Loop Programming: From Probabilistic Circuits to Loop Programming. - Viktor Pfanschilling; Hikaru Shindo; Devendra Singh Dhami; Kristian Kersting (KR, 2022)

Neural-Probabilistic Answer Set Programming. - Arseny Skryagin; Wolfgang Stammer; Daniel Ochs; Devendra Singh Dhami; Kristian Kersting (KR, 2022)

Predictive Whittle networks for time series. - Zhongjie Yu 001; Fabrizio Ventola; Nils Thoma; Devendra Singh Dhami; Martin Mundt; Kristian Kersting (UAI, 2022)

Finding Structure and Causality in Linear Programs. - Matej Zecevic; Florian Peter Busch; Devendra Singh Dhami; Kristian Kersting (CoRR, 2022)

Machines Explaining Linear Programs. - David Steinmann; 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)

Towards a Solution to Bongard Problems: A Causal Approach. - Salahedine Youssef; 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)

Can Foundation Models Talk Causality? - Moritz Willig; Matej Zecevic; 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)

LogicRank: Logic Induced Reranking for Generative Text-to-Image Systems. - Björn Deiseroth; Patrick Schramowski; Hikaru Shindo; Devendra Singh Dhami; Kristian Kersting (CoRR, 2022)

Differentiable Meta logical Programming. - Zihan Ye; Hikaru Shindo; Devendra Singh Dhami; Kristian Kersting (CoRR, 2022)

Pearl Causal Hierarchy on Image Data: Intricacies & Challenges. - Matej Zecevic; Moritz Willig; Devendra Singh Dhami; Kristian Kersting (CoRR, 2022)

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 (AAAI Bridge Program, 2023)

Vision Relation Transformer for Unbiased Scene Graph Generation. - Gopika Sudhakaran; Devendra Singh Dhami; Kristian Kersting; Stefan Roth 001 (ICCV, 2023)

Mission Design for Unmanned Aerial Vehicles using Hybrid Probabilistic Logic Programs. - Simon Kohaut; Benedict Flade; Devendra Singh Dhami; Julian Eggert; Kristian Kersting (ITSC, 2023)

Neural-Symbolic Predicate Invention: Learning Relational Concepts from Visual Scenes. - Jingyuan Sha; Hikaru Shindo; Kristian Kersting; Devendra Singh Dhami (NeSy, 2023)

Interpretable and Explainable Logical Policies via Neurally Guided Symbolic Abstraction. - Quentin Delfosse; Hikaru Shindo; Devendra Singh Dhami; Kristian Kersting (NeurIPS, 2023)

Do Not Marginalize Mechanisms, Rather Consolidate! - Moritz Willig; Matej Zecevic; Devendra Singh Dhami; Kristian Kersting (NeurIPS, 2023)

V-LoL: A Diagnostic Dataset for Visual Logical Learning. - Lukas Helff; Wolfgang Stammer; Hikaru Shindo; Devendra Singh Dhami; Kristian Kersting (CoRR, 2023)

Scalable Neural-Probabilistic Answer Set Programming. - Arseny Skryagin; Daniel Ochs; Devendra Singh Dhami; Kristian Kersting (J. Artif. Intell. Res., 2023)

Not All Causal Inference is the Same. - Matej Zecevic; Devendra Singh Dhami; Kristian Kersting (Trans. Mach. Learn. Res., 2023)

Causal Parrots: Large Language Models May Talk Causality But Are Not Causal. - Matej Zecevic; Moritz Willig; Devendra Singh Dhami; Kristian Kersting (Trans. Mach. Learn. Res., 2023)

αILP: thinking visual scenes as differentiable logic programs. - Hikaru Shindo; Viktor Pfanschilling; Devendra Singh Dhami; Kristian Kersting (Mach. Learn., 2023)

Learning Large DAGs is Harder than you Think: Many Losses are Minimal for the Wrong DAG. - Jonas Seng; Matej Zecevic; Devendra Singh Dhami; Kristian Kersting (ICLR, 2024)

StaR Maps: Unveiling Uncertainty in Geospatial Relations. - Benedict Flade; Simon Kohaut; Julian Eggert; Devendra Singh Dhami; Kristian Kersting (ITSC, 2024)

DeiSAM: Segment Anything with Deictic Prompting. - Hikaru Shindo; Manuel Brack; Gopika Sudhakaran; Devendra Singh Dhami; Patrick Schramowski; Kristian Kersting (NeurIPS, 2024)

Graph Neural Networks Need Cluster-Normalize-Activate Modules. - Arseny Skryagin; Felix Divo; Mohammad Amin Ali; Devendra Singh Dhami; Kristian Kersting (NeurIPS, 2024)

Ψnet: Efficient Causal Modeling at Scale. - Florian Peter Busch; Moritz Willig; Jonas Seng; Kristian Kersting; Devendra Singh Dhami (PGM, 2024)

χSPN: Characteristic Interventional Sum-Product Networks for Causal Inference in Hybrid Domains. - Harsh Poonia; Moritz Willig; Zhongjie Yu 001; Matej Zecevic; Kristian Kersting; Devendra Singh Dhami (UAI, 2024)

Pix2Code: Learning to Compose Neural Visual Concepts as Programs. - Antonia Wüst; Wolfgang Stammer; Quentin Delfosse; Devendra Singh Dhami; Kristian Kersting (UAI, 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)

Mission Design for Unmanned Aerial Vehicles using Hybrid Probabilistic Logic Program. - Simon Kohaut; Benedict Flade; Devendra Singh Dhami; Julian Eggert; Kristian Kersting (CoRR, 2024)

EXPIL: Explanatory Predicate Invention for Learning in Games. - Jingyuan Sha; Hikaru Shindo; Quentin Delfosse; Kristian Kersting; Devendra Singh Dhami (CoRR, 2024)

Towards Probabilistic Clearance, Explanation and Optimization. - Simon Kohaut; Benedict Flade; Devendra Singh Dhami; Julian Eggert; Kristian Kersting (CoRR, 2024)

xLSTM-Mixer: Multivariate Time Series Forecasting by Mixing via Scalar Memories. - Maurice Kraus; Felix Divo; Devendra Singh Dhami; Kristian Kersting (CoRR, 2024)

Bongard in Wonderland: Visual Puzzles that Still Make AI Go Mad? - Antonia Wüst; Tim Nelson Tobiasch; Lukas Helff; Devendra Singh Dhami; Constantin A. Rothkopf; Kristian Kersting (CoRR, 2024)

Answer Set Networks: Casting Answer Set Programming into Deep Learning. - Arseny Skryagin; Daniel Ochs; Phillip Deibert; Simon Kohaut; Devendra Singh Dhami; Kristian Kersting (CoRR, 2024)

The Constitutional Filter. - Simon Kohaut; Felix Divo; Benedict Flade; Devendra Singh Dhami; Julian Eggert; Kristian Kersting (CoRR, 2024)

Hybrid Many-Objective Optimization in Probabilistic Mission Design for Compliant and Effective UAV Routing. - Simon Kohaut; Nikolas Hohmann; Sebastian Brulin; Benedict Flade; Julian Eggert; Markus Olhofer; Jürgen Adamy; Devendra Singh Dhami; Kristian Kersting (CoRR, 2024)

Structural causal models reveal confounder bias in linear program modelling. - Matej Zecevic; Devendra Singh Dhami; Kristian Kersting (Mach. Learn., 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)

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., 2024)

Learning differentiable logic programs for abstract visual reasoning. - Hikaru Shindo; Viktor Pfanschilling; Devendra Singh Dhami; Kristian Kersting (Mach. Learn., 2024)

BlendRL: A Framework for Merging Symbolic and Neural Policy Learning. - Hikaru Shindo; Quentin Delfosse; Devendra Singh Dhami; Kristian Kersting (ICLR, 2025)

Systems with Switching Causal Relations: A Meta-Causal Perspective. - Moritz Willig; Tim Nelson Tobiasch; Florian Peter Busch; Jonas Seng; Devendra Singh Dhami; Kristian Kersting (ICLR, 2025)

Scaling Probabilistic Circuits via Data Partitioning. - Jonas Seng; Florian Peter Busch; Pooja Prasad; Devendra Singh Dhami; Martin Mundt; Kristian Kersting (UAI, 2025)

Multimodal transformer for early alarm prediction. - Nika Strem; Devendra Singh Dhami; Benedikt Schmidt; Kristian Kersting (Eng. Appl. Artif. Intell., 2025)

APT: Alarm Prediction Transformer. - Nika Strem; Devendra Singh Dhami; Benedikt Schmidt; Benjamin Klöpper; Kristian Kersting (Expert Syst. Appl., 2025)

Elucidating linear programs by neural encodings. - Florian Peter Busch; Matej Zecevic; Kristian Kersting; Devendra Singh Dhami (Frontiers Artif. Intell., 2025)

NeST: The neuro-symbolic transpiler. - Viktor Pfanschilling; Hikaru Shindo; Devendra Singh Dhami; Kristian Kersting (Int. J. Approx. Reason., 2025)

Forecasting Company Fundamentals. - Felix Divo; Eric Endress; Kevin Endler; Kristian Kersting; Devendra Singh Dhami (Trans. Mach. Learn. Res., 2025)

Probabilistic Mission Design in Neuro-Symbolic Systems. - Simon Kohaut; Benedict Flade; Daniel Ochs; Devendra Singh Dhami; Julian Eggert; Kristian Kersting (CoRR, 2025)

Exploring Neural Granger Causality with xLSTMs: Unveiling Temporal Dependencies in Complex Data. - Harsh Poonia; Felix Divo; Kristian Kersting; Devendra Singh Dhami (CoRR, 2025)

Causal Explanations Over Time: Articulated Reasoning for Interactive Environments. - Sebastian Rödling; Matej Zecevic; Devendra Singh Dhami; Kristian Kersting (CoRR, 2025)

Tagged for Direction: Pinning Down Causal Edge Directions with Precision. - Florian Peter Busch; Moritz Willig; Florian Guldan; Kristian Kersting; Devendra Singh Dhami (CoRR, 2025)

The Constitutional Controller: Doubt-Calibrated Steering of Compliant Agents. - Simon Kohaut; Felix Divo; Navid Hamid; Benedict Flade; Julian Eggert; Devendra Singh Dhami; Kristian Kersting (CoRR, 2025)