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Simon Valentin Mathis
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Cited by
Cited by
Year
Toward scalable simulations of lattice gauge theories on quantum computers
SV Mathis, G Mazzola, I Tavernelli
Physical Review D 102 (9), 094501, 2020
582020
On the expressive power of geometric graph neural networks
CK Joshi, C Bodnar, SV Mathis, T Cohen, P Lio
International Conference on Machine Learning, 15330-15355, 2023
512023
Artificial intelligence for science in quantum, atomistic, and continuum systems
X Zhang, L Wang, J Helwig, Y Luo, C Fu, Y Xie, M Liu, Y Lin, Z Xu, K Yan, ...
arXiv preprint arXiv:2307.08423, 2023
452023
Gauge-invariant quantum circuits for (1) and Yang-Mills lattice gauge theories
G Mazzola, SV Mathis, G Mazzola, I Tavernelli
Physical review research 3 (4), 043209, 2021
292021
Benchmarking Generated Poses: How Rational is Structure-based Drug Design with Generative Models?
C Harris, K Didi, AR Jamasb, CK Joshi, SV Mathis, P Lio, T Blundell
arXiv preprint arXiv:2308.07413, 2023
122023
A Hitchhiker's Guide to Geometric GNNs for 3D Atomic Systems
A Duval, SV Mathis, CK Joshi, V Schmidt, S Miret, FD Malliaros, T Cohen, ...
arXiv preprint arXiv:2312.07511, 2023
52023
Posecheck: Generative models for 3d structure-based drug design produce unrealistic poses
C Harris, K Didi, A Jamasb, C Joshi, S Mathis, P Lio, T Blundell
NeurIPS 2023 Generative AI and Biology (GenBio) Workshop, 2023
42023
Evaluating representation learning on the protein structure universe
AR Jamasb, A Morehead, Z Zhang, CK Joshi, K Didi, SV Mathis, C Harris, ...
The twelfth international conference on learning representations, 2023
32023
Diffhopp: A graph diffusion model for novel drug design via scaffold hopping
J Torge, C Harris, SV Mathis, P Lio
arXiv preprint arXiv:2308.07416, 2023
22023
Thought experiments in a quantum computer
N Nurgalieva, S Mathis, L del Rio, R Renner
arXiv preprint arXiv:2209.06236, 2022
22022
A framework for conditional diffusion modelling with applications in motif scaffolding for protein design
K Didi, F Vargas, SV Mathis, V Dutordoir, E Mathieu, UJ Komorowska, ...
arXiv preprint arXiv:2312.09236, 2023
12023
Computational tools for assessing forest recovery with GEDI shots and forest change maps
A Holcomb, SV Mathis, DA Coomes, S Keshav
Science of Remote Sensing 8, 100106, 2023
12023
Predicting protein variants with equivariant graph neural networks
A Boca, S Mathis
arXiv preprint arXiv:2306.12231, 2023
12023
Multi-state rna design with geometric multi-graph neural networks
CK Joshi, AR Jamasb, R Viñas, C Harris, S Mathis, P Liò
arXiv preprint arXiv:2305.14749, 2023
12023
Microdroplet screening rapidly profiles a biocatalyst to enable its AI-assisted engineering
M Gantz, S Mathis, F Nintzel, PJ Zurek, T Knaus, E Patel, D Boros, ...
bioRxiv, 2024.04. 08.588565, 2024
2024
gRNAde: Geometric Deep Learning for 3D RNA inverse design
CK Joshi, AR Jamasb, R Viñas, C Harris, SV Mathis, A Morehead, P Liò
bioRxiv, 2024.03. 31.587283, 2024
2024
Evaluating Zero-Shot Scoring for In Vitro Antibody Binding Prediction with Experimental Validation
D Nori, SV Mathis, A Shanehsazzadeh
arXiv preprint arXiv:2312.05273, 2023
2023
Dynamics-Informed Protein Design with Structure Conditioning
UJ Komorowska, SV Mathis, K Didi, F Vargas, P Lio, M Jamnik
The Twelfth International Conference on Learning Representations, 2023
2023
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