Yogesh Verma

Doctoral Researcher
Doctoral Researcher
T313 Dept. Computer Science
Full researcher profile
https://research.aalto.fi/...
Sähköposti
yogesh.verma@aalto.fi
Puhelinnumero
+358504070509

Osaamisalueet

113 Computer and information sciences, Computational data analysis

Palkinnot

Nokia Scholarship

The Nokia Scholarship is intended to encourage efficient, fast-progressing doctoral studies and research. Nokia Scholarships are granted to individuals pursuing a doctoral degree in Information and Communications Technologies (ICT) or in areas supporting the development of these branches of science. Scholarship can be granted for doctoral studies in a Finnish university or to a Finnish applicant for doctoral studies abroad. Optimal time for applying for the scholarship is when you have one or more accepted publications intended to be included in your dissertation. When applying for the Scholarship, you should have a good record of fast-paced, high-quality doctoral studies. The aim of the scholarship is to motivate the applicant to complete an excellent PhD project.
Award or honor granted for a specific work Department of Computer Science Jan 2024

Tutkimusryhmät

  • Professorship Garg Vikas, Doctoral Researcher

Julkaisut

E(3)-equivariant models cannot learn chirality: Field-based molecular generation

Alexandru Dumitrescu, Dani Korpela, Markus Heinonen, Yogesh Verma, Valerii Iakovlev, Vikas Garg, Harri Lähdesmäki 2025 13th International Conference on Learning Representations, ICLR 2025

Diffusion Twigs with Loop Guidance for Conditional Graph Generation

Giangiacomo Mercatali, Yogesh Verma, André Freitas, Vikas Garg 2025 Advances in Neural Information Processing Systems 37 (NeurIPS 2024)

Positional Encoding meets Persistent Homology on Graphs

Yogesh Verma, Amauri H. Souza, Vikas Garg 2025 Proceedings of Machine Learning Research

Robust Simulation-Based Inference under Missing Data via Neural Processes

Yogesh Verma, Ayush Bharti, Vikas Garg 2025 13th International Conference on Learning Representations, ICLR 2025

ClimODE: Climate and Weather Forecasting with Physics-informed Neural ODEs

Yogesh Verma, Markus Heinonen, Vikas Garg 2024 12th International Conference on Learning Representations (ICLR 2024)

Topological Neural Networks go Persistent, Equivariant, and Continuous

Yogesh Verma, Amauri H. Souza, Vikas Garg 2024 Proceedings of Machine Learning Research

AbODE: Ab initio antibody design using conjoined ODEs

Yogesh Verma, Markus Heinonen, Vikas Garg 2023 Proceedings of the 40th International Conference on Machine Learning

Modular Flows: Differential Molecular Generation

Yogesh Verma, Samuel Kaski, Markus Heinonen, Vikas Garg 2022 Advances in Neural Information Processing Systems 35 (NeurIPS 2022)