Dhami, Devendra Singh

30 publications

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

ICML 2025 Bongard in Wonderland: Visual Puzzles That Still Make AI Go Mad? Antonia Wüst, Tim Tobiasch, Lukas Helff, Inga Ibs, Wolfgang Stammer, Devendra Singh Dhami, Constantin A. Rothkopf, Kristian Kersting

NeurIPS 2025 Exploring Neural Granger Causality with xLSTMs: Unveiling Temporal Dependencies in Complex Data Harsh Poonia, Felix Divo, Kristian Kersting, Devendra Singh Dhami

ICLRW 2025 Federated Circuits: A Unified Framework for Scalable and Efficient Federated Learning Jonas Seng, Florian Peter Busch, Pooja Prasad, Devendra Singh Dhami, Martin Mundt, Kristian Kersting

TMLR 2025 Forecasting Company Fundamentals Felix Divo, Eric Endress, Kevin Endler, Kristian Kersting, Devendra Singh Dhami

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

TMLR 2025 Structural Causal Circuits: Probabilistic Circuits Climbing All Rungs of Pearl's Ladder of Causation Florian Peter Busch, Moritz Willig, Matej Zečević, Kristian Kersting, Devendra Singh Dhami

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

DMLR 2025 V-LoL: A Diagnostic Dataset for Visual Logical Learning Lukas Helff, Wolfgang Stammer, Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting

NeurIPS 2025 When Causal Dynamics Matter: Adapting Causal Strategies Through Meta-Aware Interventions Moritz Willig, Tim Tobiasch, Devendra Singh Dhami, Kristian Kersting

NeurIPS 2025 xLSTM-Mixer: Multivariate Time Series Forecasting by Mixing via Scalar Memories Maurice Kraus, Felix Divo, Devendra Singh Dhami, Kristian Kersting

PGM 2024 $Ψ$net: Efficient Causal Modeling at Scale Florian Peter Busch, Moritz Willig, Jonas Seng, Kristian Kersting, Devendra Singh Dhami

UAI 2024 $χ$SPN: Characteristic Interventional Sum-Product Networks for Causal Inference in Hybrid Domains Harsh Poonia, Moritz Willig, Zhongjie Yu, Matej Ze\vcević, Kristian Kersting, Devendra Singh Dhami

NeurIPSW 2024 Bongard in Wonderland: Visual Puzzles That Still Make AI Go Mad? Antonia Wüst, Tim Tobiasch, Lukas Helff, Devendra Singh Dhami, Constantin A. Rothkopf, Kristian Kersting

NeurIPS 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

MLJ 2024 Learning Differentiable Logic Programs for Abstract Visual Reasoning Hikaru Shindo, Viktor Pfanschilling, Devendra Singh Dhami, Kristian Kersting

ICLR 2024 Learning Large DAGs Is Harder than You Think: Many Losses Are Minimal for the Wrong DAG Jonas Seng, Matej Zečević, Devendra Singh Dhami, Kristian Kersting

UAI 2024 Pix2Code: Learning to Compose Neural Visual Concepts as Programs Antonia Wüst, Wolfgang Stammer, Quentin Delfosse, Devendra Singh Dhami, Kristian Kersting

MLJ 2024 Structural Causal Models Reveal Confounder Bias in Linear Program Modelling Matej Zecevic, Devendra Singh Dhami, Kristian Kersting

NeurIPSW 2024 Systems with Switching Causal Relations: A Meta-Causal Perspective Moritz Willig, Tim Tobiasch, Florian Peter Busch, Jonas Seng, Devendra Singh Dhami, Kristian Kersting

TMLR 2023 Causal Parrots: Large Language Models May Talk Causality but Are Not Causal Matej Zečević, Moritz Willig, Devendra Singh Dhami, Kristian Kersting

TMLR 2023 Not All Causal Inference Is the Same Matej Zečević, Devendra Singh Dhami, Kristian Kersting

JAIR 2023 Scalable Neural-Probabilistic Answer Set Programming Arseny Skryagin, Daniel Ochs, Devendra Singh Dhami, Kristian Kersting

ICCV 2023 Vision Relation Transformer for Unbiased Scene Graph Generation Gopika Sudhakaran, Devendra Singh Dhami, Kristian Kersting, Stefan Roth

MLJ 2023 αILP: Thinking Visual Scenes as Differentiable Logic Programs Hikaru Shindo, Viktor Pfanschilling, Devendra Singh Dhami, Kristian Kersting

ICLRW 2022 Finding Structure and Causality in Linear Programs Matej Zečević, Florian Peter Busch, Devendra Singh Dhami, Kristian Kersting

UAI 2022 Predictive Whittle Networks for Time Series Zhongjie Yu, Fabrizio Ventola, Nils Thoma, Devendra Singh Dhami, Martin Mundt, Kristian Kersting

NeurIPSW 2020 The Curious Case of Stacking Boosted Relational Dependency Networks Siwen Yan, Devendra Singh Dhami, Sriraam Natarajan

AAAI 2019 Fast Relational Probabilistic Inference and Learning: Approximate Counting via Hypergraphs Mayukh Das, Devendra Singh Dhami, Gautam Kunapuli, Kristian Kersting, Sriraam Natarajan