8 citations · 19 across the 6 of their papers we have counts for
6 papers
Does AI Understand Imaging? A Systematic Benchmark of Agentic AI for Computational Imaging Tasks
Ethan Chung, Chuanjun Zheng, Jasper Tan +3
Vision-language models (VLMs) and agentic AI have shown strong performance on semantic visual tasks, but it remains unclear whether they can handle the physics and inverse problems…
WIRE: Wavelet Implicit Neural Representations
Vishwanath Saragadam, Daniel LeJeune, Jasper Tan +3
Implicit neural representations (INRs) have recently advanced numerous vision-related areas. INR performance depends strongly on the choice of the nonlinear activation function emp…
A Blessing of Dimensionality in Membership Inference through Regularization
Jasper Tan, Daniel LeJeune, Blake Mason +2
Is overparameterization a privacy liability? In this work, we study the effect that the number of parameters has on a classifier's vulnerability to membership inference attacks. We…
MINER: Multiscale Implicit Neural Representations
Vishwanath Saragadam, Jasper Tan, Guha Balakrishnan +2
We introduce a new neural signal model designed for efficient high-resolution representation of large-scale signals. The key innovation in our multiscale implicit neural representa…
Parameters or Privacy: A Provable Tradeoff Between Overparameterization and Membership Inference
Jasper Tan, Blake Mason, Hamid Javadi +1
A surprising phenomenon in modern machine learning is the ability of a highly overparameterized model to generalize well (small error on the test data) even when it is trained to m…
Wearing a MASK: Compressed Representations of Variable-Length Sequences Using Recurrent Neural Tangent Kernels
Sina Alemohammad, Hossein Babaei, Randall Balestriero +8
High dimensionality poses many challenges to the use of data, from visualization and interpretation, to prediction and storage for historical preservation. Techniques abound to red…