Frederik Wenkel

According to our database, Frederik Wenkel authored at least 21 papers between 2020 and 2026.

Collaborative distances:

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

2026

Can Computational Reducibility Lead to Transferable Models for Graph Combinatorial Optimization?

Semih Cantürk, Thomas Sabourin, Frederik Wenkel, Michael Perlmutter, Guy Wolf

CoRR, March, 2026

2025

TxPert: Leveraging Biochemical Relationships for Out-of-Distribution Transcriptomic Perturbation Prediction.

Frederik Wenkel, Wilson Tu, Cassandra Masschelein, Hamed Shirzad, Cian Eastwood, Shawn Whitfield, Ihab Bendidi, Craig Russell, Liam Hodgson, Yassir El Mesbahi, Jiarui Ding, Marta M. Fay, Berton Earnshaw, Emmanuel Noutahi, Alisandra Kaye Denton

CoRR, May, 2025

2024

Learnable Filters for Geometric Scattering Modules.

Alexander Tong, Frederik Wenkel, Dhananjay Bhaskar, Kincaid MacDonald, Jackson D. Grady, Michael Perlmutter, Smita Krishnaswamy, Guy Wolf

IEEE Trans. Signal Process., 2024

How Molecules Impact Cells: Unlocking Contrastive PhenoMolecular Retrieval.

Philip Fradkin, Puria Azadi, Karush Suri, Frederik Wenkel, Ali Bashashati, Maciej Sypetkowski, Dominique Beaini

CoRR, 2024

Towards a General GNN Framework for Combinatorial Optimization.

Frederik Wenkel, Semih Cantürk, Michael Perlmutter, Guy Wolf

CoRR, 2024

On the Scalability of GNNs for Molecular Graphs.

Maciej Sypetkowski, Frederik Wenkel, Farimah Poursafaei, Nia Dickson, Karush Suri, Philip Fradkin, Dominique Beaini

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

How Molecules Impact Cells: Unlocking Contrastive PhenoMolecular Retrieval.

Philip Fradkin, Puria Azadi Moghadam, Karush Suri, Frederik Wenkel, Ali Bashashati, Maciej Sypetkowski, Dominique Beaini

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Towards a General Recipe for Combinatorial Optimization With Multi-Filter GNNs.

Frederik Wenkel, Semih Cantürk, Stefan Horoi, Michael Perlmutter, Guy Wolf

Proceedings of the Learning on Graphs Conference, 26-29 November 2024, Virtual., 2024

Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets.

Dominique Beaini, Shenyang Huang, Joao Alex Cunha, Zhiyi Li, Gabriela Moisescu-Pareja, Oleksandr Dymov, Samuel Maddrell-Mander, Callum McLean, Frederik Wenkel, Luis Müller, Jama Hussein Mohamud, Ali Parviz, Michael Craig, Michal Koziarski, Jiarui Lu, Zhaocheng Zhu, Cristian Gabellini, Kerstin Klaser, Josef Dean, Cas Wognum, Maciej Sypetkowski, Guillaume Rabusseau, Reihaneh Rabbany, Jian Tang, Christopher Morris, Mirco Ravanelli, Guy Wolf, Prudencio Tossou, Hadrien Mary, Therence Bois, Andrew W. Fitzgibbon, Blazej Banaszewski, Chad Martin, Dominic Masters

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets.

Dominique Beaini, Shenyang Huang, Joao Alex Cunha, Zhiyi Li, Gabriela Moisescu-Pareja, Oleksandr Dymov, Samuel Maddrell-Mander, Callum McLean, Frederik Wenkel, Luis Müller, Jama Hussein Mohamud, Ali Parviz, Michael Craig, Michal Koziarski, Jiarui Lu, Zhaocheng Zhu, Cristian Gabellini, Kerstin Klaser, Josef Dean, Cas Wognum, Maciej Sypetkowski, Guillaume Rabusseau, Reihaneh Rabbany, Jian Tang, Christopher Morris, Ioannis Koutis, Mirco Ravanelli, Guy Wolf, Prudencio Tossou, Hadrien Mary, Therence Bois, Andrew W. Fitzgibbon, Blazej Banaszewski, Chad Martin, Dominic Masters

CoRR, 2023

Inferring dynamic regulatory interaction graphs from time series data with perturbations.

Dhananjay Bhaskar, Daniel Sumner Magruder, Edward De Brouwer, Aarthi Venkat, Frederik Wenkel, Guy Wolf, Smita Krishnaswamy

CoRR, 2023

Inferring Dynamic Regulatory Interaction Graphs From Time Series Data With Perturbations.

Dhananjay Bhaskar, Daniel Sumner Magruder, Matheo Morales, Edward De Brouwer, Aarthi Venkat, Frederik Wenkel, Guy Wolf, Smita Krishnaswamy

Proceedings of the Learning on Graphs Conference, 27-30 November 2023, Virtual Event., 2023

2022

Taxonomy of Benchmarks in Graph Representation Learning.

Renming Liu, Semih Cantürk, Frederik Wenkel, Dylan Sandfelder, Devin Kreuzer, Anna Little, Sarah McGuire, Leslie O'Bray, Michael Perlmutter, Bastian Rieck, Matthew J. Hirn, Guy Wolf, Ladislav Rampásek

CoRR, 2022

Can Hybrid Geometric Scattering Networks Help Solve the Maximal Clique Problem?

Yimeng Min, Frederik Wenkel, Michael Perlmutter, Guy Wolf

CoRR, 2022

Overcoming Oversmoothness in Graph Convolutional Networks via Hybrid Scattering Networks.

Frederik Wenkel, Yimeng Min, Matthew J. Hirn, Michael Perlmutter, Guy Wolf

CoRR, 2022

Can Hybrid Geometric Scattering Networks Help Solve the Maximum Clique Problem?

Yimeng Min, Frederik Wenkel, Michael Perlmutter, Guy Wolf

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Taxonomy of Benchmarks in Graph Representation Learning.

Renming Liu, Semih Cantürk, Frederik Wenkel, Sarah McGuire, Xinyi Wang, Anna Little, Leslie O'Bray, Michael Perlmutter, Bastian Rieck, Matthew J. Hirn, Guy Wolf, Ladislav Rampásek

Proceedings of the Learning on Graphs Conference, 2022

2021

Towards a Taxonomy of Graph Learning Datasets.

Renming Liu, Semih Cantürk, Frederik Wenkel, Dylan Sandfelder, Devin Kreuzer, Anna Little, Sarah McGuire, Leslie O'Bray, Michael Perlmutter, Bastian Rieck, Matthew J. Hirn, Guy Wolf, Ladislav Rampásek

CoRR, 2021

Geometric Scattering Attention Networks.

Yimeng Min, Frederik Wenkel, Guy Wolf

Proceedings of the IEEE International Conference on Acoustics, 2021

2020

Data-Driven Learning of Geometric Scattering Networks.

Alexander Tong, Frederik Wenkel, Kincaid MacDonald, Smita Krishnaswamy, Guy Wolf

CoRR, 2020

Scattering GCN: Overcoming Oversmoothness in Graph Convolutional Networks.

Yimeng Min, Frederik Wenkel, Guy Wolf

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020