1 citations · 2 across the 5 of their papers we have counts for
8 papers
Approximate Message Passing for Quantum State Tomography
Noah Siekierski, Kausthubh Chandramouli, Christian Kümmerle +2
Quantum state tomography (QST) is an indispensable tool for characterizing many-body quantum systems. However, due to the exponential scaling of the cost of the protocol with syste…
Q3R: Quadratic Reweighted Rank Regularizer for Effective Low-Rank Training
Ipsita Ghosh, Ethan Nguyen, Christian Kümmerle
Parameter-efficient training based on low-rank optimization has become a highly successful tool for fine-tuning large deep learning models. However, these methods often fail for lo…
Sample-Efficient Geometry Reconstruction from Euclidean Distances using Non-Convex Optimization
Ipsita Ghosh, Abiy Tasissa, Christian Kümmerle
The problem of finding suitable point embedding or geometric configurations given only Euclidean distance information of point pairs arises both as a core task and as a sub-problem…
An Exposition of Pathfinding Strategies Within Lightning Network Clients
Sindura Saraswathi, Christian Kümmerle
The Lightning Network is a peer-to-peer network designed to address Bitcoin's scalability challenges, facilitating rapid, cost-effective, and instantaneous transactions through bid…
Sparse Recovery for Overcomplete Frames: Sensing Matrices and Recovery Guarantees
Xuemei Chen, Christian Kümmerle, Rongrong Wang
Signal models formed as linear combinations of few atoms from an over-complete dictionary or few frame vectors from a redundant frame have become central to many applications in hi…
Dictionary-Sparse Recovery From Heavy-Tailed Measurements
Pedro Abdalla, Christian Kümmerle
The recovery of signals that are sparse not in a basis, but rather sparse with respect to an over-complete dictionary is one of the most flexible settings in the field of compresse…
On the geometry of polytopes generated by heavy-tailed random vectors
Olivier Guédon, Felix Krahmer, Christian Kümmerle +2
We study the geometry of centrally-symmetric random polytopes, generated by independent copies of a random vector taking values in . We show that under minima…
The Oracle of DLphi
Dominik Alfke, Weston Baines, Jan Blechschmidt +24
We present a novel technique based on deep learning and set theory which yields exceptional classification and prediction results. Having access to a sufficiently large amount of l…