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ORCIDDavid van Dijk
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2020 – today
- 2024
[c18]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:
BrainLM: A foundation model for brain activity recordings. ICLR 2024- [c17]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:
Cell2Sentence: Teaching Large Language Models the Language of Biology. ICML 2024 - [i18]Shiyang Zhang, Aakash Patel, Syed Asad Rizvi, Nianchen Liu, Sizhuang He, Amin Karbasi, Emanuele Zappala, David van Dijk:
Intelligence at the Edge of Chaos. CoRR abs/2410.02536 (2024) - 2023
- [c16]Emanuele Zappala, Antonio Henrique de Oliveira Fonseca, Andrew Henry Moberly, Michael James Higley, Chadi Abdallah, Jessica A. Cardin, David van Dijk:
Neural Integro-Differential Equations. AAAI 2023: 11104-11112 - [c15]Antonio Henrique de Oliveira Fonseca, Emanuele Zappala, Josue Ortega Caro, David van Dijk:
Continuous Spatiotemporal Transformer. ICML 2023: 7343-7365 - [i17]Antonio Henrique de Oliveira Fonseca, Emanuele Zappala, Josue Ortega Caro, David van Dijk:
Continuous Spatiotemporal Transformers. CoRR abs/2301.13338 (2023) - [i16]Emanuele Zappala, Daniel LeVine, Sizhuang He, Syed Asad Rizvi, Sacha Levy, David van Dijk:
Operator Learning Meets Numerical Analysis: Improving Neural Networks through Iterative Methods. CoRR abs/2310.01618 (2023) - 2022
- [i15]Emanuele Zappala, Antonio Henrique de Oliveira Fonseca, Andrew Henry Moberly, Michael James Higley, Chadi Abdallah, Jessica A. Cardin, David van Dijk:
Neural Integro-Differential Equations. CoRR abs/2206.14282 (2022) - [i14]Emanuele Zappala, Antonio Henrique de Oliveira Fonseca, Josue Ortega Caro, David van Dijk:
Neural Integral Equations. CoRR abs/2209.15190 (2022) - [i13]Syed Asad Rizvi, Nhi Nguyen, Haoran Lyu, Ben Christensen, Josue Ortega Caro, Emanuele Zappala, Maria Brbic, Rahul Madhav Dhodapkar, David van Dijk:
AMPNet: Attention as Message Passing for Graph Neural Networks. CoRR abs/2210.09475 (2022) - 2021
- [j2]Matthew Amodio, Dennis L. Shung, Daniel B. Burkhardt, Patrick Wong, Michael Simonov, Yu Yamamoto, David van Dijk, Francis Perry Wilson, Akiko Iwasaki, Smita Krishnaswamy:
Generating hard-to-obtain information from easy-to-obtain information: Applications in drug discovery and clinical inference. Patterns 2(7): 100288 (2021) - [c14]Arijit Sehanobish, Neal G. Ravindra, David van Dijk:
Gaining Insight into SARS-CoV-2 Infection and COVID-19 Severity Using Self-supervised Edge Features and Graph Neural Networks. AAAI 2021: 4864-4873 - [c13]Arijit Sehanobish, Hector H. Corzo, Onur Kara, David van Dijk:
Learning Potentials of Quantum Systems using Deep Neural Networks. AAAI Spring Symposium: MLPS 2021 - 2020
- [c12]Neal G. Ravindra, Arijit Sehanobish, Jenna L. Pappalardo, David A. Hafler, David van Dijk:
Disease state prediction from single-cell data using graph attention networks. CHIL 2020: 121-130 - [c11]Alexander Tong, Jessie Huang, Guy Wolf, David van Dijk, Smita Krishnaswamy:
TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics. ICML 2020: 9526-9536 - [c10]Alexander Tong, David van Dijk, Jay S. Stanley III, Matthew Amodio, Kristina Yim, Rebecca Muhle, James Noonan, Guy Wolf, Smita Krishnaswamy:
Interpretable Neuron Structuring with Graph Spectral Regularization. IDA 2020: 509-521 - [c9]Matthew Amodio, David van Dijk, Guy Wolf, Smita Krishnaswamy:
Learning General Transformations of Data for Out-of-Sample Extensions. MLSP 2020: 1-6 - [i12]Alexander Tong, Jessie Huang, Guy Wolf, David van Dijk, Smita Krishnaswamy:
TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics. CoRR abs/2002.04461 (2020) - [i11]Neal G. Ravindra, Arijit Sehanobish, Jenna L. Pappalardo, David A. Hafler, David van Dijk:
Disease State Prediction From Single-Cell Data Using Graph Attention Networks. CoRR abs/2002.07128 (2020) - [i10]Antonio H. O. Fonseca, David van Dijk:
Learning aligned embeddings for semi-supervised word translation using Maximum Mean Discrepancy. CoRR abs/2006.11578 (2020) - [i9]Arijit Sehanobish, Neal G. Ravindra, David van Dijk:
Gaining insight into SARS-CoV-2 infection and COVID-19 severity using self-supervised edge features and Graph Neural Networks. CoRR abs/2006.12971 (2020) - [i8]Arijit Sehanobish, Hector H. Corzo, Onur Kara, David van Dijk:
Learning Potentials of Quantum Systems using Deep Neural Networks. CoRR abs/2006.13297 (2020) - [i7]Arijit Sehanobish, Neal G. Ravindra, David van Dijk:
Self-supervised edge features for improved Graph Neural Network training. CoRR abs/2007.04777 (2020) - [i6]Arijit Sehanobish, Neal G. Ravindra, David van Dijk:
Permutation invariant networks to learn Wasserstein metrics. CoRR abs/2010.05820 (2020)
2010 – 2019
- 2019
- [c8]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:
Coarse Graining of Data via Inhomogeneous Diffusion Condensation. IEEE BigData 2019: 2624-2633 - [c7]David van Dijk, Daniel B. Burkhardt, Matthew Amodio, Alexander Tong, Guy Wolf, Smita Krishnaswamy:
Finding Archetypal Spaces Using Neural Networks. IEEE BigData 2019: 2634-2643 - [c6]David van Dijk, Marco Ferrante, Nicola Ferro, Evangelos Kanoulas:
A Markovian Approach to Evaluate Session-Based IR Systems. ECIR (1) 2019: 621-635 - [i5]David van Dijk, Daniel B. Burkhardt, Matthew Amodio, Alexander Tong, Guy Wolf, Smita Krishnaswamy:
Finding Archetypal Spaces for Data Using Neural Networks. CoRR abs/1901.09078 (2019) - [i4]Scott Gigante, Jay S. Stanley III, Ngan Vu, David van Dijk, Kevin R. Moon, Guy Wolf, Smita Krishnaswamy:
Compressed Diffusion. CoRR abs/1902.00033 (2019) - [i3]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:
Coarse Graining of Data via Inhomogeneous Diffusion Condensation. CoRR abs/1907.04463 (2019) - 2018
- [i2]David van Dijk, Scott Gigante, Alexander Strzalkowski, Guy Wolf, Smita Krishnaswamy:
Modeling Dynamics with Deep Transition-Learning Networks. CoRR abs/1802.03497 (2018) - [i1]Alexander Tong, David van Dijk, Jay S. Stanley III, Matthew Amodio, Guy Wolf, Smita Krishnaswamy:
Graph Spectral Regularization for Neural Network Interpretability. CoRR abs/1810.00424 (2018) - 2015
- [c5]David van Dijk, Manos Tsagkias, Maarten de Rijke:
Early Detection of Topical Expertise in Community Question Answering. SIGIR 2015: 995-998 - [c4]David van Dijk, Zhaochun Ren, Evangelos Kanoulas, Maarten de Rijke:
The University of Amsterdam (ILPS) at TREC 2015 Total Recall Track. TREC 2015 - 2014
- [c3]David Graus, David van Dijk, Manos Tsagkias, Wouter Weerkamp, Maarten de Rijke:
Recipient recommendation in enterprises using communication graphs and email content. SIGIR 2014: 1079-1082 - 2013
- [c2]Zhaochun Ren, David van Dijk, David Graus, Nina van der Knaap, Hans Henseler, Maarten de Rijke:
Semantic Linking and Contextualization for Social Forensic Text Analysis. EISIC 2013: 96-99 - 2010
- [j1]David van Dijk, Gökhan Ertaylan, Charles A. B. Boucher, Peter M. A. Sloot:
Identifying potential survival strategies of HIV-1 through virus-host protein interaction networks. BMC Syst. Biol. 4: 96 (2010) - [c1]David van Dijk, Peter M. A. Sloot, J. C. Tay, Martijn C. Schut:
Individual-based simulation of sexual selection: A quantitative genetic approach. ICCS 2010: 2003-2011
Coauthor Index
aka: Antonio Henrique de Oliveira Fonseca
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