About Me
I’m a Doctoral Researcher at (Qurious) Quantum Machine Learners, Aalto University, working with Prof. Vikas Garg, Prof. Samuel Kaski and Dr. Markus Heinonen. I am also a recipient of Nokia Scholarship and a DAAD AI-Net Fellow.
My research interests include physics-inspired deep learning for modeling dynamical systems, (geometric and topological) deep learning, generative models and robust bayesian inference.
More about me here.
Publications
- Y. Verma*, G. Mercatali*, A. Freitas and V. Garg. “Diffusion Twigs with Loop Guidance for Conditional Graph Generation”, 38th Conference on Neural Information Processing Systems (NeurIPS 2024).
- Y. Verma, A. Souza and V. Garg. “Topological Neural Networks go Persistent, Equivariant and Continuous”, 41st International Conference on Machine Learning (ICML 2024). arxiv
- Y. Verma, M. Heinonen and V. Garg. “ClimODE: Climate Forecasting With Physics-informed Neural ODEs”, Oral (Top 1%) , 12th International Conference on Learning Representations (ICLR 2024). arxiv
- Y. Verma, M. Heinonen and V. Garg. “AbODE: Ab initio Antibody Design using Conjoined ODEs.”, 40th International Conference on Machine Learning (ICML 2023). arxiv
- Y. Verma, S. Kaski, M. Heinonen and V. Garg. “Modular Flows: Differential Molecular Generation.”, 36th Conference on Neural Information Processing Systems (NeurIPS 2022). arxiv
- Y. Verma, M. Aggarwal, V. Joshi, A. Sharma. “Characterization Study of a Button BPM with an Approach to Automated Measurements”, 9th International Beam Instrumentation Conference, IBIC2020., arxiv
Preprints
- A. Dumitrescu, D. Korpela, M. Heinonen, Y. Verma, V. Iakovlev, V. Garg, H. Lähdesmäki. “Field-based Molecule Generation”, preprint
- Y. Verma and S. Jena. “Particle Track Reconstruction using Geometric Deep Learning “, preprint
- Y. Verma and S. Jena. “Jet characterization in Heavy Ion Collisions by QCD-Aware Graph Neural Networks”, preprint
- Y. Verma and S. Jena. “Shower Identification in Calorimeter using Deep Learning “, preprint
Workshops:
- Y. Verma, M. Heinonen and V. Garg. “AbODE: Ab initio Antibody Design using Conjoined ODEs.”, New Frontiers in
Learning, Control, and Dynamical Systems at ICML 2023.
- Y. Verma, S. Kaski, M. Heinonen and V. Garg. “Modular Flows: Differential Molecular Generation.”, Symbiosis of Deep Learning and Differential Equations, Workshop at NeurIPS 2022.
- Y. Verma, S. Kaski, M. Heinonen and V. Garg. “Modular Flows: Differential Molecular Generation.”, New Frontiers in Graph Learning, Workshop at NeurIPS 2022.
Services
Reviewing:
- NeurIPS
- ICML
- ICLR
- RBCDSAI-FCAI Conference
Email:
firstname.lastname@aalto.fi
Address:
A338, Tietotekniikka-talo (CS building)
Konemiehentie 2
FI-02150
Espoo
Finland