10 papers
Flexible Online Representation Learning Based on Similarity Matching
Shagesh Sridharan, Yanis Bahroun, Anirvan M. Sengupta
Sparse high-dimensional representations are conducive to uncovering nontrivial structures in unsupervised exploration of data. Such a representation can deal with the dense connect…
Reading Qubits with Sequential Weak Measurements: Limits of Information Extraction
Cesar Lema, Aleix Bou-Comas, Atithi Acharya +2
Quantum information processing and computation requires high accuracy qubit configuration readout. In many practical schemes, the initial qubit configuration has to be inferred fro…
Attention as In-Context Empirical Bayes: A Two-Stage View via Particle Dynamics
Matthew Smart, Soumya Ganguly, Nilava Metya +2
We study minimal attention-only transformers under all-token corruption and show they admit a two-stage empirical Bayes interpretation. A single attention step computes a kernel-we…
Beyond Variational Bias: Resolving Intertwined Orders in the Hubbard Model
Luciano Loris Viteritti, Riccardo Rende, Christopher Roth +3
The two-dimensional Hubbard model at finite doping hosts competing or intertwined orders, resulting in conflicting conclusions from different computational approaches regarding its…
Double descent: When do neural quantum states generalize?
M. Schuyler Moss, Alev Orfi, Christopher Roth +5
Neural quantum states (NQS) provide flexible and compact wavefunction parameterizations for numerical studies of quantum many-body physics. In particular, NQS aim to circumvent the…
A Network of Biologically Inspired Rectified Spectral Units (ReSUs) Learns Hierarchical Features Without Error Backpropagation
Shanshan Qin, Joshua L. Pughe-Sanford, Alexander Genkin +4
We introduce a biologically inspired, multilayer neural architecture composed of Rectified Spectral Units (ReSUs). Each ReSU projects a recent window of its input history onto a ca…