1 citations · 2 across the 11 of their papers we have counts for
14 papers
Inducing Fourier Geometry: A Smoothness Prior Imposes Approximate Translation Equivariance in Multimodal Stellar Embeddings
Ilay Kamai, Alex M. Bronstein, Hagai B. Perets
Learned representations often contain geometric structure induced by symmetries in the underlying data. We ask whether a known continuous parameter space can instead be used to \em…
The Residual Stream's Effective Depth
Barak Gahtan, Ido Galil, Alex M. Bronstein
We introduce \emph{effective depth} ($\Deff$), a scalar diagnostic that treats the layer-wise residual stream of a transformer as a discrete-time process, measures how representati…
Invertible Query-Key Coupling Composes with Attention Mechanisms
Barak Gahtan, Alex M. Bronstein
Scaled dot-product attention forms its queries and keys as independent linear projections, so the two never interact before the dot product that scores them. We study coupled query…
Differentiable Randers-Finsler Eikonal Solvers
Barak Gahtan, Jacob Shpund, Alex M. Bronstein
Fast and differentiable solvers for anisotropic and asymmetric distance fields are a key primitive in geometry processing, enabling gradient-based optimization over metrics, drift…
DigiArm: An Anthropomorphic 3D-Printed Prosthetic Hand with Enhanced Dexterity for Typing Tasks
Dean Zadok, Tom Naamani, Yuval Bar-Ratson +5
Despite recent advancements, existing prosthetic limbs are unable to replicate the dexterity and intuitive control of the human hand. Current control systems for prosthetic hands a…
Effective Sample Size and Generalization Bounds for Temporal Networks
Barak Gahtan, Alex M. Bronstein
Learning from time series is fundamentally different from learning from i.i.d.\ data: temporal dependence can make long sequences effectively information-poor, yet standard evaluat…
Machine-learning inference of stellar properties using integrated photometric and spectroscopic data
Ilay Kamai, Alex M. Bronstein, Hagai B. Perets
Stellar astrophysics relies on diverse observational modalities-primarily photometric light curves and spectroscopic data from which fundamental stellar properties are inferred. Wh…
Smart Ankleband for Plug-and-Play Hand-Prosthetic Control
Dean Zadok, Oren Salzman, Alon Wolf +1
Building robotic prostheses requires a sensor-based interface designed to provide the robotic hand with the control required to perform hand gestures. Traditional Electromyography…
Data-Driven Cellular Network Selector for Vehicle Teleoperations
Barak Gahtan, Reuven Cohen, Alex M. Bronstein +1
Remote control of robotic systems, also known as teleoperation, is crucial for the development of autonomous vehicle (AV) technology. It allows a remote operator to view live video…
Beyond the Alphabet: Deep Signal Embedding for Enhanced DNA Clustering
Hadas Abraham, Barak Gahtan, Adir Kobovich +3
The emerging field of DNA storage employs strands of DNA bases (A/T/C/G) as a storage medium for digital information to enable massive density and durability. The DNA storage pipel…
Estimating the Number of HTTP/3 Responses in QUIC Using Deep Learning
Barak Gahtan, Robert J. Shahla, Reuven Cohen +1
QUIC, a new and increasingly used transport protocol, enhances TCP by offering improved security, performance, and stream multiplexing. These features, however, also impose challen…
WearableMil: An End-to-End Framework for Military Activity Recognition and Performance Monitoring
Barak Gahtan, Shany Funk, Einat Kodesh +3
Musculoskeletal injuries during military training significantly impact readiness, making prevention through activity monitoring crucial. While Human Activity Recognition (HAR) usin…
Exploring QUIC Dynamics: A Large-Scale Dataset for Encrypted Traffic Analysis
Barak Gahtan, Robert J. Shahla, Alex M. Bronstein +1
The increasing adoption of the QUIC transport protocol has transformed encrypted web traffic, necessitating new methodologies for network analysis. However, existing datasets lack…
Do We Need Depth in State-Of-The-Art Face Authentication?
Amir Livne, Alex Bronstein, Ron Kimmel +2
Some face recognition methods are designed to utilize geometric information extracted from depth sensors to overcome the weaknesses of single-image based recognition technologies.…