Search Results for author:
Found 6 papers, 3 papers with code
Spectroscopy-Guided Discovery of Three-Dimensional Structures of Disordered Materials with Diffusion Models
In this work, we introduce a new framework based on the diffusion model, a recent generative machine learning method to predict 3D structures of disordered materials from a target property.
TUTORING: Instruction-Grounded Conversational Agent for Language Learners
In this paper, we propose Tutoring bot, a generative chatbot trained on a large scale of tutor-student conversations for English-language learning.
Guidelines for the Regularization of Gammas in Batch Normalization for Deep Residual Networks
L2 regularization for weights in neural networks is widely used as a standard training trick.
Ranked #2 on
Text Classification
on GLUE SST2
Improved Robustness of Vision Transformer via PreLayerNorm in Patch Embedding
We compared the robustness of CNN and ViT by assuming various image corruptions that may appear in practical vision tasks.
Dead Pixel Test Using Effective Receptive Field
First, we evaluated the size of the receptive field.
Ranked #5 on
Fine-Grained Image Classification
on Caltech-101
Metadynamics sampling in atomic environment space for collecting training data for machine learning potentials
The universal mathematical form of machine-learning potentials (MLPs) shifts the core of development of interatomic potentials to collecting proper training data.
Computational Physics
