Identifying potential survival strategies of HIV-1 through virus-host protein interaction networks. - David van Dijk; Gökhan Ertaylan; Charles A. B. Boucher; Peter M. A. Sloot (BMC Syst. Biol., 2010)

Individual-based simulation of sexual selection: A quantitative genetic approach. - David van Dijk; Peter M. A. Sloot; J. C. Tay; Martijn C. Schut (ICCS, 2010)

Semantic Linking and Contextualization for Social Forensic Text Analysis. - Zhaochun Ren; David van Dijk; David Graus; Nina van der Knaap; Hans Henseler; Maarten de Rijke (EISIC, 2013)

Recipient recommendation in enterprises using communication graphs and email content. - David Graus; David van Dijk; Manos Tsagkias; Wouter Weerkamp; Maarten de Rijke (SIGIR, 2014)

Early Detection of Topical Expertise in Community Question Answering. - David van Dijk; Manos Tsagkias; Maarten de Rijke (SIGIR, 2015)

The University of Amsterdam (ILPS) at TREC 2015 Total Recall Track. - David van Dijk; Zhaochun Ren; Evangelos Kanoulas; Maarten de Rijke (TREC, 2015)

Modeling Dynamics with Deep Transition-Learning Networks. - David van Dijk; Scott Gigante; Alexander Strzalkowski; Guy Wolf; Smita Krishnaswamy (CoRR, 2018)

Graph Spectral Regularization for Neural Network Interpretability. - Alexander Tong 001; David van Dijk; Jay S. Stanley III; Matthew Amodio; Guy Wolf; Smita Krishnaswamy (CoRR, 2018)

Coarse Graining of Data via Inhomogeneous Diffusion Condensation. - 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 (IEEE BigData, 2019)

Finding Archetypal Spaces Using Neural Networks. - David van Dijk; Daniel B. Burkhardt; Matthew Amodio; Alexander Tong 001; Guy Wolf; Smita Krishnaswamy (IEEE BigData, 2019)

A Markovian Approach to Evaluate Session-Based IR Systems. - David van Dijk; Marco Ferrante; Nicola Ferro 001; Evangelos Kanoulas (ECIR (1), 2019)

Finding Archetypal Spaces for Data Using Neural Networks. - David van Dijk; Daniel B. Burkhardt; Matthew Amodio; Alexander Tong 001; Guy Wolf; Smita Krishnaswamy (CoRR, 2019)

Compressed Diffusion. - Scott Gigante; Jay S. Stanley III; Ngan Vu; David van Dijk; Kevin R. Moon; Guy Wolf; Smita Krishnaswamy (CoRR, 2019)

Disease state prediction from single-cell data using graph attention networks. - Neal G. Ravindra; Arijit Sehanobish; Jenna L. Pappalardo; David A. Hafler; David van Dijk (CHIL, 2020)

TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics. - Alexander Tong 001; Jessie Huang; Guy Wolf; David van Dijk; Smita Krishnaswamy (ICML, 2020)

Interpretable Neuron Structuring with Graph Spectral Regularization. - Alexander Tong 001; David van Dijk; Jay S. Stanley III; Matthew Amodio; Kristina Yim; Rebecca Muhle; James Noonan; Guy Wolf; Smita Krishnaswamy (IDA, 2020)

Learning General Transformations of Data for Out-of-Sample Extensions. - Matthew Amodio; David van Dijk; Guy Wolf; Smita Krishnaswamy (MLSP, 2020)

Learning aligned embeddings for semi-supervised word translation using Maximum Mean Discrepancy. - Antonio H. O. Fonseca; David van Dijk (CoRR, 2020)

Self-supervised edge features for improved Graph Neural Network training. - Arijit Sehanobish; Neal G. Ravindra; David van Dijk (CoRR, 2020)

Permutation invariant networks to learn Wasserstein metrics. - Arijit Sehanobish; Neal G. Ravindra; David van Dijk (CoRR, 2020)

Gaining Insight into SARS-CoV-2 Infection and COVID-19 Severity Using Self-supervised Edge Features and Graph Neural Networks. - Arijit Sehanobish; Neal G. Ravindra; David van Dijk (AAAI, 2021)

Learning Potentials of Quantum Systems using Deep Neural Networks. - Arijit Sehanobish; Hector H. Corzo; Onur Kara; David van Dijk (AAAI Spring Symposium: MLPS, 2021)

Generating hard-to-obtain information from easy-to-obtain information: Applications in drug discovery and clinical inference. - Matthew Amodio; Dennis L. Shung; Daniel B. Burkhardt; Patrick Wong; Michael Simonov; Yu Yamamoto; David van Dijk; Francis Perry Wilson; Akiko Iwasaki; Smita Krishnaswamy (Patterns, 2021)

Neural Integral Equations. - Emanuele Zappala; Antonio Henrique de Oliveira Fonseca; Josue Ortega Caro; David van Dijk (CoRR, 2022)

AMPNet: Attention as Message Passing for Graph Neural Networks. - Syed Asad Rizvi; Nhi Nguyen; Haoran Lyu; Ben Christensen; Josue Ortega Caro; Emanuele Zappala; Maria Brbic; Rahul Madhav Dhodapkar; David van Dijk (CoRR, 2022)

Neural Integro-Differential Equations. - Emanuele Zappala; Antonio Henrique de Oliveira Fonseca; Andrew Henry Moberly; Michael James Higley; Chadi Abdallah; Jessica A. Cardin; David van Dijk (AAAI, 2023)

Continuous Spatiotemporal Transformer. - Antonio Henrique de Oliveira Fonseca; Emanuele Zappala; Josue Ortega Caro; David van Dijk (ICML, 2023)

Continuous Spatiotemporal Transformers. - Antonio Henrique de Oliveira Fonseca; Emanuele Zappala; Josue Ortega Caro; David van Dijk (CoRR, 2023)

Operator Learning Meets Numerical Analysis: Improving Neural Networks through Iterative Methods. - Emanuele Zappala; Daniel LeVine; Sizhuang He; Syed Asad Rizvi; Sacha Levy; David van Dijk (CoRR, 2023)

BrainLM: A foundation model for brain activity recordings. - 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 (ICLR, 2024)

Cell2Sentence: Teaching Large Language Models the Language of Biology. - 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; et al. (ICML, 2024)

CaLMFlow: Volterra Flow Matching using Causal Language Models. - Sizhuang He; Daniel LeVine; Ivan Vrkic; Marco Francesco Bressana; David Zhang; Syed Asad Rizvi; Yangtian Zhang; Emanuele Zappala; David van Dijk (CoRR, 2024)

HEART: Learning better representation of EHR data with a heterogeneous relation-aware transformer. - Tinglin Huang; Syed Asad Rizvi; Rohan Krishna Thakur; Vimig Socrates; Meili Gupta; David van Dijk; R. Andrew Taylor; Rex Ying (J. Biomed. Informatics, 2024)

Learning integral operators via neural integral equations. - Emanuele Zappala; Antonio Henrique de Oliveira Fonseca; Josue Ortega Caro; Andrew Henry Moberly; Michael James Higley; Jessica A. Cardin; David van Dijk (Nat. Mac. Intell., 2024)

Intelligence at the Edge of Chaos. - Shiyang Zhang; Aakash Patel; Syed Asad Rizvi; Nianchen Liu; Sizhuang He; Amin Karbasi; Emanuele Zappala; David van Dijk (ICLR, 2025)

COAST: Intelligent Time-Adaptive Neural Operators. - Zhikai Wu; Shiyang Zhang; Sizhuang He; Sifan Wang; Min Zhu; Anran Jiao; Lu Lu; David van Dijk (CoRR, 2025)

Non-Markovian Discrete Diffusion with Causal Language Models. - Yangtian Zhang; Sizhuang He; Daniel LeVine; Lawrence Zhao; David Zhang; Syed Asad Rizvi; Emanuele Zappala; Rex Ying; David van Dijk (CoRR, 2025)