Search Results for author:
Found 10 papers, 3 papers with code
PhyDeformer: High-Quality Non-Rigid Garment Registration with Physics-Awareness
We present PhyDeformer, a new deformation method for high-quality garment mesh registration.
Benchmarking Large Language Model Volatility
The impact of non-deterministic outputs from Large Language Models (LLMs) is not well examined for financial text understanding tasks.
Quantifying Impairment and Disease Severity Using AI Models Trained on Healthy Subjects
We applied the COBRA score to address a key limitation of current clinical evaluation of upper-body impairment in stroke patients.
Improved selective background Monte Carlo simulation at Belle II with graph attention networks and weighted events
When measuring rare processes at Belle II, a huge luminosity is required, which means a large number of simulations are necessary to determine signal efficiencies and background contributions.
Doubly Stochastic Models: Learning with Unbiased Label Noises and Inference Stability
While previous studies primarily focus on the affects of label noises to the performance of learning, our work intends to investigate the implicit regularization effects of the label noises, under mini-batch sampling settings of stochastic gradient descent (SGD), with assumptions that label noises are unbiased.
4D Facial Expression Diffusion Model
In this paper, we introduce a generative framework for generating 3D facial expression sequences (i. e. 4D faces) that can be conditioned on different inputs to animate an arbitrary 3D face mesh.
Handling Inter-class and Intra-class Imbalance in Class-imbalanced Learning
Class-imbalance is a common problem in machine learning practice.
Deep Probability Estimation
Reliable probability estimation is of crucial importance in many real-world applications where there is inherent (aleatoric) uncertainty.
Gravitational perturbations from NHEK to Kerr
Our aim is to characterise those perturbations that are responsible for the deviations away from extremality, and to contrast them with the linearized perturbations treated in the Newman-Penrose formalism.
High Energy Physics - Theory General Relativity and Quantum Cosmology
Implicit Regularization Effects of Unbiased Random Label Noises with SGD
Random label noises (or observational noises) widely exist in practical machinelearning settings.
