David van Dijk

According to our database, David van Dijk authored at least 35 papers between 2010 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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

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

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

Intelligence at the Edge of Chaos.

Shiyang Zhang, Aakash Patel, Syed Asad Rizvi, Nianchen Liu, Sizhuang He, Amin Karbasi, Emanuele Zappala, David van Dijk

CoRR, 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, Insu Han, Antonio Henrique de Oliveira Fonseca, Josue Ortega Caro, Amin Karbasi, Rahul Madhav Dhodapkar, David van Dijk

Proceedings of the Forty-first International Conference on Machine Learning, 2024

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 Cross, Prateek Mittal, Emanuele Zappala, Rahul Madhav Dhodapkar, Chadi Abdallah, David van Dijk

Proceedings of the Twelfth International Conference on Learning Representations, 2024

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

Continuous Spatiotemporal Transformers.

Antonio Henrique de Oliveira Fonseca, Emanuele Zappala, Josue Ortega Caro, David van Dijk

CoRR, 2023

Continuous Spatiotemporal Transformer.

Antonio Henrique de Oliveira Fonseca, Emanuele Zappala, Josue Ortega Caro, David van Dijk

Proceedings of the International Conference on Machine Learning, 2023

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

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

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 Integral Equations.

Emanuele Zappala, Antonio Henrique de Oliveira Fonseca, Josue Ortega Caro, David van Dijk

CoRR, 2022

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

Learning Potentials of Quantum Systems using Deep Neural Networks.

Arijit Sehanobish, Hector H. Corzo, Onur Kara, David van Dijk

Proceedings of the AAAI 2021 Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physical Sciences, Stanford, CA, USA, March 22nd - to, 2021

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

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Permutation invariant networks to learn Wasserstein metrics.

Arijit Sehanobish, Neal G. Ravindra, 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

Learning aligned embeddings for semi-supervised word translation using Maximum Mean Discrepancy.

Antonio H. O. Fonseca, David van Dijk

CoRR, 2020

Learning General Transformations of Data for Out-of-Sample Extensions.

Matthew Amodio, David van Dijk, Guy Wolf, Smita Krishnaswamy

Proceedings of the 30th IEEE International Workshop on Machine Learning for Signal Processing, 2020

Interpretable Neuron Structuring with Graph Spectral Regularization.

Alexander Tong, David van Dijk, Jay S. Stanley III, Matthew Amodio, Kristina Yim, Rebecca Muhle, James Noonan, Guy Wolf, Smita Krishnaswamy

Proceedings of the Advances in Intelligent Data Analysis XVIII, 2020

TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics.

Alexander Tong, Jessie Huang, Guy Wolf, David van Dijk, Smita Krishnaswamy

Proceedings of the 37th International Conference on Machine Learning, 2020

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

Proceedings of the ACM CHIL '20: ACM Conference on Health, 2020

2019

Compressed Diffusion.

Scott Gigante, Jay S. Stanley III, Ngan Vu, David van Dijk, Kevin R. Moon, Guy Wolf, Smita Krishnaswamy

CoRR, 2019

Finding Archetypal Spaces for Data Using Neural Networks.

David van Dijk, Daniel B. Burkhardt, Matthew Amodio, Alexander Tong, Guy Wolf, Smita Krishnaswamy

CoRR, 2019

A Markovian Approach to Evaluate Session-Based IR Systems.

David van Dijk, Marco Ferrante, Nicola Ferro, Evangelos Kanoulas

Proceedings of the Advances in Information Retrieval, 2019

Finding Archetypal Spaces Using Neural Networks.

David van Dijk, Daniel B. Burkhardt, Matthew Amodio, Alexander Tong, Guy Wolf, Smita Krishnaswamy

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

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

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018

Graph Spectral Regularization for Neural Network Interpretability.

Alexander Tong, David van Dijk, Jay S. Stanley III, Matthew Amodio, Guy Wolf, Smita Krishnaswamy

CoRR, 2018

Modeling Dynamics with Deep Transition-Learning Networks.

David van Dijk, Scott Gigante, Alexander Strzalkowski, Guy Wolf, Smita Krishnaswamy

CoRR, 2018

2015

The University of Amsterdam (ILPS) at TREC 2015 Total Recall Track.

David van Dijk, Zhaochun Ren, Evangelos Kanoulas, Maarten de Rijke

Proceedings of The Twenty-Fourth Text REtrieval Conference, 2015

Early Detection of Topical Expertise in Community Question Answering.

David van Dijk, Manos Tsagkias, Maarten de Rijke

Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2015

2014

Recipient recommendation in enterprises using communication graphs and email content.

David Graus, David van Dijk, Manos Tsagkias, Wouter Weerkamp, Maarten de Rijke

Proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2014

2013

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

Proceedings of the 2013 European Intelligence and Security Informatics Conference, 2013

2010

Individual-based simulation of sexual selection: A quantitative genetic approach.

David van Dijk, Peter M. A. Sloot, J. C. Tay, Martijn C. Schut

Proceedings of the International Conference on Computational Science, 2010

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