Hemanth Saratchandran
Australian Institute for Machine Learning - Projects
Faculty of Sciences, Engineering and Technology
I am a mathematician primarily working in the areas of Artificial Intelligence, Deep Learning, Geometric Analysis and Topology.
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Appointments
Date Position Institution name 2022 - ongoing Research Fellow Australian Institute of Machine Learning 2020 - 2022 Laureate Research Associate University of Adelaide 2019 - 2020 Scientific Assistant (Wissenschaftlicher Mitarbeiter, TV-L 13, full time) University of Augsburg 2016 - 2018 Postdoctoral Research Fellow Beijing International Centre for Mathematical Research -
Language Competencies
Language Competency English Can read, write, speak, understand spoken and peer review -
Education
Date Institution name Country Title 2011 - 2016 Univeristy of Oxford United Kingdom Dphil 2006 - 2010 Australian National University Australia Bachelors of Advanced Science (with Honours) -
Research Interests
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Journals
Year Citation 2024 Saratchandran, H., Chng, S. -F., & Lucey, S. (2024). Architectural Strategies for the optimization of Physics-Informed Neural Networks.. CoRR, abs/2402.02711. 2023 Bandara, L., Goffeng, M., & Saratchandran, H. (2023). Realisations of elliptic operators on compact manifolds with boundary. Advances in Mathematics, 420, 108968.
2023 Hochs, P., & Saratchandran, H. (2023). A Ruelle dynamical zeta function for equivariant flows. 2023 Ramasinghe, S., Saratchandran, H., Shevchenko, V., & Lucey, S. (2023). On the effectiveness of neural priors in modeling dynamical systems.. CoRR, abs/2303.05728. 2022 Milatovic, O., & Saratchandran, H. (2022). Generalized Ornstein–Uhlenbeck semigroups in weighted Lp-spaces on Riemannian manifolds. Journal of Functional Analysis, 283(8), 62 pages.
2022 Saratchandran, H., Zhang, J., & Zhang, P. (2022). A New Higher Order Yang-Mills-Higgs Flow on Riemannian 4-Manifolds. Bulletin of the Australian Mathematical Society, 107(2), 320-329.
2022 Hochs, P., & Saratchandran, H. (2022). Equivariant analytic torsion for proper actions. 2022 Ramasinghe, S., MacDonald, L. E., Farazi, M. R., Saratchandran, H., & Lucey, S. (2022). How You Start Matters for Generalization.. CoRR, abs/2206.08558. 2021 MacDonald, L., Mathai, V., & Saratchandran, H. (2021). On the Chern character in Higher Twisted K-theory and spherical T-duality. Communications in Mathematical Physics, 385(1), 331-368.
Scopus12021 Saratchandran, H. (2021). Essential self-adjointness of perturbed quadharmonic operators on Riemannian manifolds with an application to the separation problem. Mathematische Nachrichten, 294(5), 997-1044.
Scopus1 WoS12021 Milatovic, O., & Saratchandran, H. (2021). Essential Self-Adjointness of Perturbed Biharmonic Operators via Conformally Transformed Metrics. Potential Analysis, 56(4), 623-647.
2019 Saratchandran, H. (2019). Higher order Seiberg–Witten functionals and their associated gradient flows. Manuscripta Mathematica, 160(3-4), 411-481.
Scopus2 WoS22019 Milatovic, O., & Saratchandran, H. (2019). Inequalities and separation for covariant Schrödinger operators. Journal of Geometry and Physics, 138, 215-222.
Scopus2 WoS22018 Saratchandran, H. (2018). Finite volume hyperbolic complements of 2-tori and Klein bottles in closed smooth simply connected 4-manifolds. New York Journal of Mathematics, 24, 443-450.
Scopus2 WoS12017 Bandara, L., & Saratchandran, H. (2017). Essential self-adjointness of powers of first-order differential operators on non-compact manifolds with low-regularity metrics. Journal of Functional Analysis, 273(12), 3719-3758.
Scopus6 WoS62016 Saratchandran, H. (2016). Kirby diagrams and the Ratcliffe-Tschantz hyperbolic 4-manifolds. Topology and its Applications, 202, 301-317.
Scopus1 WoS12015 Saratchandran, H. (2015). A four dimensional hyperbolic link complement in a standard $S^4$. 2015 Saratchandran, H. (2015). A four dimensional hyperbolic link complement in a standard $S^2 \times
S^2$.2015 Saratchandran, H. (2015). Complements of tori in $\#_{2k}S^2 \times S^2$ that admit a hyperbolic
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Conference Papers
Year Citation 2023 Saratchandran, H., Chng, S. -F., Ramasinghe, S., MacDonald, L. E., & Lucey, S. (2023). Curvature-Aware Training for Coordinate Networks.. In CoRR Vol. abs/2305.08552. 2023 Ramasinghe, S., MacDonald, L., Farazi, M., Saratchandran, H., & Lucey, S. (2023). How Much does Initialization Affect Generalization?. In ICML'23: Proceedings of the 40th International Conference on Machine Learning Vol. 202 (pp. 28637-28655). Honolulu, Hawaii, USA: Association for Computing Machinery. ACM.
Scopus12023 MacDonald, L. E., Valmadre, J., Saratchandran, H., & Lucey, S. (2023). On skip connections and normalisation layers in deep optimisation.. In A. Oh, T. Naumann, A. Globerson, K. Saenko, M. Hardt, & S. Levine (Eds.), NeurIPS. 2023 Saratchandran, H., Chng, S. F., Ramasinghe, S., MacDonald, L., & Lucey, S. (2023). Curvature-Aware Training for Coordinate Networks. In Proceedings of the IEEE International Conference on Computer Vision (pp. 13282-13292). FRANCE, Paris: IEEE COMPUTER SOC.
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Working Paper
Year Citation 2022 MacDonald, L. E., Saratchandran, H., Valmadre, J., & Lucey, S. (2022). A global analysis of global optimisation.. -
Preprint
Year Citation 2024 Chng, S. -F., Saratchandran, H., & Lucey, S. (2024). Preconditioners for the Stochastic Training of Implicit Neural
Representations.2024 Saratchandran, H., Ramasinghe, S., Shevchenko, V., Long, A., & Lucey, S. (2024). A Sampling Theory Perspective on Activations for Implicit Neural
Representations.2024 Saratchandran, H., Ramasinghe, S., & Lucey, S. (2024). From Activation to Initialization: Scaling Insights for Optimizing
Neural Fields.2024 Ji, Y., Saratchandran, H., Gordon, C., Zhang, Z., & Lucey, S. (2024). Sine Activated Low-Rank Matrices for Parameter Efficient Learning. 2024 Gordon, C., MacDonald, L. E., Saratchandran, H., & Lucey, S. (2024). D'OH: Decoder-Only random Hypernetworks for Implicit Neural
Representations.2024 Saratchandran, H., Chng, S. -F., & Lucey, S. (2024). Architectural Strategies for the optimization of Physics-Informed Neural
Networks.2024 Saratchandran, H., Chng, S. -F., & Lucey, S. (2024). Analyzing the Neural Tangent Kernel of Periodically Activated Coordinate
Networks.
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