David van Dijk

48 papers A* 9B 1Misc 1Journal 29Unranked 8

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Learning Permutation Distributions via Reflected Diffusion on Ranks. CoRR Sizhuang He, Yangtian Zhang, Shiyang Zhang, David van Dijk
2026	J	`jnl`	STRIDE: Post-Training LLMs to Reason and Refine Bio-Sequences via Edit Trajectories. CoRR Daiheng Zhang, Shiyang Zhang, Sizhuang He, Yangtian Zhang, Syed Asad Rizvi, David van Dijk
2026	J	`jnl`	SciDesignBench: Benchmarking and Improving Language Models for Scientific Inverse Design. CoRR David van Dijk, Ivan Vrkic
2025	J	`jnl`	COAST: Intelligent Time-Adaptive Neural Operators. CoRR Zhikai Wu, Shiyang Zhang, Sizhuang He, Sifan Wang, Min Zhu, Anran Jiao, Lu Lu, David van Dijk
2025	J	`jnl`	GeoFunFlow: Geometric Function Flow Matching for Inverse Operator Learning over Complex Geometries. CoRR Sifan Wang, Zhikai Wu, David van Dijk, Lu Lu
2025	A*	`conf`	Intelligence at the Edge of Chaos. ICLR Shiyang Zhang, Aakash Patel, Syed Asad Rizvi, Nianchen Liu, Sizhuang He, Amin Karbasi, Emanuele Zappala, David van Dijk
2025	J	`jnl`	Non-Markovian Discrete Diffusion with Causal Language Models. CoRR Yangtian Zhang, Sizhuang He, Daniel LeVine, Lawrence Zhao, David Zhang, Syed Asad Rizvi, Emanuele Zappala, Rex Ying, David van Dijk
2024	A*	`conf`	BrainLM: A foundation model for brain activity recordings. ICLR Josue Ortega Caro, Antonio Henrique de Oliveira Fonseca, Syed Asad Rizvi, Matteo Rosati, Christopher L. Averill, James L. Cross, Prateek Mittal, Emanuele Zappala, Rahul Madhav Dhodapkar, Chadi Abdallah, David van Dijk
2024	J	`jnl`	CaLMFlow: Volterra Flow Matching using Causal Language Models. CoRR Sizhuang He, Daniel LeVine, Ivan Vrkic, Marco Francesco Bressana, David Zhang, Syed Asad Rizvi, Yangtian Zhang, Emanuele Zappala, David van Dijk
2024	A*	`conf`	Cell2Sentence: Teaching Large Language Models the Language of Biology. ICML Daniel LeVine, Syed Asad Rizvi, Sacha Lévy, Nazreen Pallikkavaliyaveetil, David Zhang, Xingyu Chen, Sina Ghadermarzi, Ruiming Wu, Zihe Zheng, Ivan Vrkic, Anna Zhong, Daphne Raskin, Insu Han, Antonio Henrique de Oliveira Fonseca, Josue Ortega Caro, Amin Karbasi, Rahul Madhav Dhodapkar, David van Dijk
2024	J	`jnl`	HEART: Learning better representation of EHR data with a heterogeneous relation-aware transformer. J. Biomed. Informatics Tinglin Huang, Syed Asad Rizvi, Rohan Krishna Thakur, Vimig Socrates, Meili Gupta, David van Dijk, R. Andrew Taylor, Rex Ying
2024	J	`jnl`	Intelligence at the Edge of Chaos. CoRR Shiyang Zhang, Aakash Patel, Syed Asad Rizvi, Nianchen Liu, Sizhuang He, Amin Karbasi, Emanuele Zappala, David van Dijk
2024	J	`jnl`	Learning integral operators via neural integral equations. Nat. Mac. Intell. Emanuele Zappala, Antonio Henrique de Oliveira Fonseca, Josue Ortega Caro, Andrew Henry Moberly, Michael James Higley, Jessica A. Cardin, David van Dijk
2023	A*	`conf`	Continuous Spatiotemporal Transformer. ICML Antonio Henrique de Oliveira Fonseca, Emanuele Zappala, Josue Ortega Caro, David van Dijk
2023	J	`jnl`	Continuous Spatiotemporal Transformers. CoRR Antonio Henrique de Oliveira Fonseca, Emanuele Zappala, Josue Ortega Caro, David van Dijk
2023	A*	`conf`	Neural Integro-Differential Equations. AAAI Emanuele Zappala, Antonio Henrique de Oliveira Fonseca, Andrew Henry Moberly, Michael James Higley, Chadi Abdallah, Jessica A. Cardin, David van Dijk
2023	J	`jnl`	Operator Learning Meets Numerical Analysis: Improving Neural Networks through Iterative Methods. CoRR Emanuele Zappala, Daniel LeVine, Sizhuang He, Syed Asad Rizvi, Sacha Levy, David van Dijk
2022	J	`jnl`	AMPNet: Attention as Message Passing for Graph Neural Networks. CoRR Syed Asad Rizvi, Nhi Nguyen, Haoran Lyu, Ben Christensen, Josue Ortega Caro, Emanuele Zappala, Maria Brbic, Rahul Madhav Dhodapkar, David van Dijk
2022	J	`jnl`	Neural Integral Equations. CoRR Emanuele Zappala, Antonio Henrique de Oliveira Fonseca, Josue Ortega Caro, David van Dijk
2022	J	`jnl`	Neural Integro-Differential Equations. CoRR Emanuele Zappala, Antonio Henrique de Oliveira Fonseca, Andrew Henry Moberly, Michael James Higley, Chadi Abdallah, Jessica A. Cardin, David van Dijk
2021	A*	`conf`	Gaining Insight into SARS-CoV-2 Infection and COVID-19 Severity Using Self-supervised Edge Features and Graph Neural Networks. AAAI Arijit Sehanobish, Neal G. Ravindra, David van Dijk
2021	J	`jnl`	Generating hard-to-obtain information from easy-to-obtain information: Applications in drug discovery and clinical inference. Patterns Matthew Amodio, Dennis L. Shung, Daniel B. Burkhardt, Patrick Wong, Michael Simonov, Yu Yamamoto, David van Dijk, Francis Perry Wilson, Akiko Iwasaki, Smita Krishnaswamy
2021	—	`conf`	Learning Potentials of Quantum Systems using Deep Neural Networks. AAAI Spring Symposium: MLPS Arijit Sehanobish, Hector H. Corzo, Onur Kara, David van Dijk
2020	J	`jnl`	Disease State Prediction From Single-Cell Data Using Graph Attention Networks. CoRR Neal G. Ravindra, Arijit Sehanobish, Jenna L. Pappalardo, David A. Hafler, David van Dijk
2020	—	`conf`	Disease state prediction from single-cell data using graph attention networks. CHIL Neal G. Ravindra, Arijit Sehanobish, Jenna L. Pappalardo, David A. Hafler, David van Dijk
2020	J	`jnl`	Gaining insight into SARS-CoV-2 infection and COVID-19 severity using self-supervised edge features and Graph Neural Networks. CoRR Arijit Sehanobish, Neal G. Ravindra, David van Dijk
2020	B	`conf`	Interpretable Neuron Structuring with Graph Spectral Regularization. IDA Alexander Tong, David van Dijk, Jay S. Stanley III, Matthew Amodio, Kristina Yim, Rebecca Muhle, James Noonan, Guy Wolf, Smita Krishnaswamy
2020	—	`conf`	Learning General Transformations of Data for Out-of-Sample Extensions. MLSP Matthew Amodio, David van Dijk, Guy Wolf, Smita Krishnaswamy
2020	J	`jnl`	Learning Potentials of Quantum Systems using Deep Neural Networks. CoRR Arijit Sehanobish, Hector H. Corzo, Onur Kara, David van Dijk
2020	J	`jnl`	Learning aligned embeddings for semi-supervised word translation using Maximum Mean Discrepancy. CoRR Antonio H. O. Fonseca, David van Dijk
2020	J	`jnl`	Permutation invariant networks to learn Wasserstein metrics. CoRR Arijit Sehanobish, Neal G. Ravindra, David van Dijk
2020	J	`jnl`	Self-supervised edge features for improved Graph Neural Network training. CoRR Arijit Sehanobish, Neal G. Ravindra, David van Dijk
2020	A*	`conf`	TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics. ICML Alexander Tong, Jessie Huang, Guy Wolf, David van Dijk, Smita Krishnaswamy
2020	J	`jnl`	TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics. CoRR Alexander Tong, Jessie Huang, Guy Wolf, David van Dijk, Smita Krishnaswamy
2019	—	`conf`	A Markovian Approach to Evaluate Session-Based IR Systems. ECIR (1) David van Dijk, Marco Ferrante, Nicola Ferro, Evangelos Kanoulas
2019	—	`conf`	Coarse Graining of Data via Inhomogeneous Diffusion Condensation. IEEE BigData Nathan Brugnone, Smita Krishnaswamy, Alex Gonopolskiy, Mark W. Moyle, Manik Kuchroo, David van Dijk, Kevin R. Moon, Daniel Colón-Ramos, Guy Wolf, Matthew J. Hirn
2019	J	`jnl`	Coarse Graining of Data via Inhomogeneous Diffusion Condensation. CoRR Nathan Brugnone, Alex Gonopolskiy, Mark W. Moyle, Manik Kuchroo, David van Dijk, Kevin R. Moon, Daniel Colón-Ramos, Guy Wolf, Matthew J. Hirn, Smita Krishnaswamy
2019	J	`jnl`	Compressed Diffusion. CoRR Scott Gigante, Jay S. Stanley III, Ngan Vu, David van Dijk, Kevin R. Moon, Guy Wolf, Smita Krishnaswamy
2019	—	`conf`	Finding Archetypal Spaces Using Neural Networks. IEEE BigData David van Dijk, Daniel B. Burkhardt, Matthew Amodio, Alexander Tong, Guy Wolf, Smita Krishnaswamy
2019	J	`jnl`	Finding Archetypal Spaces for Data Using Neural Networks. CoRR David van Dijk, Daniel B. Burkhardt, Matthew Amodio, Alexander Tong, Guy Wolf, Smita Krishnaswamy
2018	J	`jnl`	Graph Spectral Regularization for Neural Network Interpretability. CoRR Alexander Tong, David van Dijk, Jay S. Stanley III, Matthew Amodio, Guy Wolf, Smita Krishnaswamy
2018	J	`jnl`	Modeling Dynamics with Deep Transition-Learning Networks. CoRR David van Dijk, Scott Gigante, Alexander Strzalkowski, Guy Wolf, Smita Krishnaswamy
2015	A*	`conf`	Early Detection of Topical Expertise in Community Question Answering. SIGIR David van Dijk, Manos Tsagkias, Maarten de Rijke
2015	—	`conf`	The University of Amsterdam (ILPS) at TREC 2015 Total Recall Track. TREC David van Dijk, Zhaochun Ren, Evangelos Kanoulas, Maarten de Rijke
2014	A*	`conf`	Recipient recommendation in enterprises using communication graphs and email content. SIGIR David Graus, David van Dijk, Manos Tsagkias, Wouter Weerkamp, Maarten de Rijke
2013	—	`conf`	Semantic Linking and Contextualization for Social Forensic Text Analysis. EISIC Zhaochun Ren, David van Dijk, David Graus, Nina van der Knaap, Hans Henseler, Maarten de Rijke
2010	J	`jnl`	Identifying potential survival strategies of HIV-1 through virus-host protein interaction networks. BMC Syst. Biol. David van Dijk, Gökhan Ertaylan, Charles A. B. Boucher, Peter M. A. Sloot
2010	Misc	`conf`	Individual-based simulation of sexual selection: A quantitative genetic approach. ICCS David van Dijk, Peter M. A. Sloot, J. C. Tay, Martijn C. Schut