7 papers
Stochastic Counterdiabatic Driving via Biorthogonal Liouvillian Eigenmodes
Sandeep Suresh Cranganore, Sebastian Lehner, Johannes Brandstetter +1
Finite-time driving of stochastic systems generates excess dissipation, causing the evolving probability distribution to lag behind the instantaneous equilibrium, and consequently…
ANTIC: Adaptive Neural Temporal In-situ Compressor
Sandeep S. Cranganore, Andrei Bodnar, Gianluca Galletti +2
The persistent storage requirements for high-resolution, spatiotemporally evolving fields governed by large-scale and high-dimensional partial differential equations (PDEs) have re…
Einstein Fields: A Neural Perspective To Computational General Relativity
Sandeep Suresh Cranganore, Andrei Bodnar, Arturs Berzins +1
We introduce Einstein Fields, a neural representation designed to compress computationally intensive four-dimensional numerical relativity simulations into compact implicit neural…
Physics-Informed Neural Compression of High-Dimensional Plasma Data
Gianluca Galletti, Gerald Gutenbrunner, Sandeep S. Cranganore +6
High-fidelity scientific simulations are now producing unprecedented amounts of data, creating a storage and analysis bottleneck. A single simulation can generate tremendous data v…
Whole Genome Transformer for Gene Interaction Effects in Microbiome Habitat Specificity
Zhufeng Li, Sandeep S Cranganore, Nicholas Youngblut +1
Leveraging the vast genetic diversity within microbiomes offers unparalleled insights into complex phenotypes, yet the task of accurately predicting and understanding such traits f…
Exploring Channel Distinguishability in Local Neighborhoods of the Model Space in Quantum Neural Networks
Sabrina Herbst, Sandeep Suresh Cranganore, Vincenzo De Maio +1
With the increasing interest in Quantum Machine Learning, Quantum Neural Networks (QNNs) have emerged and gained significant attention. These models have, however, been shown to be…