154 citations · 717 across the 63 of their papers we have counts for
5 papers · 1 filter
Excess risk analysis for epistemic uncertainty with application to variational inference
Futoshi Futami, Tomoharu Iwata, Naonori Ueda +2
Bayesian deep learning plays an important role especially for its ability evaluating epistemic uncertainty (EU). Due to computational complexity issues, approximation methods such…
Analyzing Lottery Ticket Hypothesis from PAC-Bayesian Theory Perspective
Keitaro Sakamoto, Issei Sato
The lottery ticket hypothesis (LTH) has attracted attention because it can explain why over-parameterized models often show high generalization ability. It is known that when we us…
Goldilocks-curriculum Domain Randomization and Fractal Perlin Noise with Application to Sim2Real Pneumonia Lesion Detection
Takahiro Suzuki, Shouhei Hanaoka, Issei Sato
A computer-aided detection (CAD) system based on machine learning is expected to assist radiologists in making a diagnosis. It is desirable to build CAD systems for the various typ…
Empirical Evaluation and Theoretical Analysis for Representation Learning: A Survey
Kento Nozawa, Issei Sato
Representation learning enables us to automatically extract generic feature representations from a dataset to solve another machine learning task. Recently, extracted feature repre…
Neural Lagrangian Schrödinger Bridge: Diffusion Modeling for Population Dynamics
Takeshi Koshizuka, Issei Sato
Population dynamics is the study of temporal and spatial variation in the size of populations of organisms and is a major part of population ecology. One of the main difficulties i…