:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Kim, Bum Jun, Kim, Sang Woo
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2501.17683
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Configuring Data Augmentations to Reduce Variance Shift in Positional Embedding of Vision Transformers
by: Kim, Bum Jun, et al.
Published: (2024)

Stochastic Subsampling With Average Pooling
by: Kim, Bum Jun, et al.
Published: (2024)

The Disappearance of Timestep Embedding in Modern Time-Dependent Neural Networks
by: Kim, Bum Jun, et al.
Published: (2024)

Per-Loss Adapters for Gradient Conflict in Physics-Informed Neural Networks
by: Kim, Bum Jun, et al.
Published: (2026)

Exactness Matters for Physical Rule Enforcement
by: Kim, Bum Jun
Published: (2026)

Prediction Loss Guided Decision-Focused Learning
by: Jeon, Haeun, et al.
Published: (2025)

Safe Semi-Supervised Contrastive Learning Using In-Distribution Data as Positive Examples
by: Kwak, Min Gu, et al.
Published: (2024)

Locally Convex Global Loss Network for Decision-Focused Learning
by: Jeon, Haeun, et al.
Published: (2024)

CaliMatch: Adaptive Calibration for Improving Safe Semi-supervised Learning
by: Bae, Jinsoo, et al.
Published: (2025)

Scale Equalization for Multi-Level Feature Fusion
by: Kim, Bum Jun, et al.
Published: (2024)

Radial Müntz-Szász Networks: Neural Architectures with Learnable Power Bases for Multidimensional Singularities
by: N'guessan, Gnankan Landry Regis, et al.
Published: (2026)

Discovering Scaling Exponents with Physics-Informed Müntz-Szász Networks
by: N'guessan, Gnankan Landry Regis, et al.
Published: (2026)

FlowBot: Inducing LLM Workflows with Bilevel Optimization and Textual Gradients
by: Yu, Hongyeon, et al.
Published: (2026)

Riemannian Denoising Model for Molecular Structure Optimization with Chemical Accuracy
by: Woo, Jeheon, et al.
Published: (2024)

Relaxed Contrastive Learning for Federated Learning
by: Seo, Seonguk, et al.
Published: (2024)

SimO Loss: Anchor-Free Contrastive Loss for Fine-Grained Supervised Contrastive Learning
by: Bouhsine, Taha, et al.
Published: (2024)

EqOD: Symmetry-Informed Stability Selection for PDE Identification
by: N'guessan, Gnankan Landry Regis, et al.
Published: (2026)

Approximation Rates in Besov Norms and Sample-Complexity of Kolmogorov-Arnold Networks with Residual Connections
by: Kratsios, Anastasis, et al.
Published: (2025)

Pretraining with Random Noise for Fast and Robust Learning without Weight Transport
by: Cheon, Jeonghwan, et al.
Published: (2024)

Discrete Diffusion Schrödinger Bridge Matching for Graph Transformation
by: Kim, Jun Hyeong, et al.
Published: (2024)

Pareto Inverse Reinforcement Learning for Diverse Expert Policy Generation
by: Kim, Woo Kyung, et al.
Published: (2024)

Leveraging Federated Learning for Automatic Detection of Clopidogrel Treatment Failures
by: Kim, Samuel, et al.
Published: (2024)

ContrastCAD: Contrastive Learning-based Representation Learning for Computer-Aided Design Models
by: Jung, Minseop, et al.
Published: (2024)

Unlocking Noise-Resistant Vision: Key Architectural Secrets for Robust Models
by: Kim, Bum Jun, et al.
Published: (2025)

Improving Diffusion-Based Image Editing Faithfulness via Guidance and Scheduling
by: Cho, Hansam, et al.
Published: (2025)

Probabilistic Variational Contrastive Learning
by: Jeong, Minoh, et al.
Published: (2025)

OC-Distill: Ontology-aware Contrastive Learning with Cross-Modal Distillation for ICU Risk Prediction
by: Liang, Zhongyuan, et al.
Published: (2026)

Decoupled Contrastive Learning for Federated Learning
by: Kim, Hyungbin, et al.
Published: (2025)

Advanced Torrential Loss Function for Precipitation Forecasting
by: Choi, Jaeho, et al.
Published: (2025)

Residual Koopman Spectral Profiling for Predicting and Preventing Transformer Training Instability
by: Kim, Bum Jun, et al.
Published: (2026)

Can Contrastive Learning Refine Embeddings
by: Liu, Lihui, et al.
Published: (2024)

Optimal Control of Multiclass Fluid Queueing Networks: A Machine Learning Approach
by: Bertsimas, Dimitris, et al.
Published: (2023)

QuadNorm: Resolution-Robust Normalization for Neural Operators
by: Kim, Bum Jun, et al.
Published: (2026)

Analysis of Using Sigmoid Loss for Contrastive Learning
by: Lee, Chungpa, et al.
Published: (2024)

Sample Selection via Contrastive Fragmentation for Noisy Label Regression
by: Kim, Chris Dongjoo, et al.
Published: (2025)

Anomaly Detection in Power Grids via Context-Agnostic Learning
by: Park, SangWoo, et al.
Published: (2024)

Robust Policy Learning via Offline Skill Diffusion
by: Kim, Woo Kyung, et al.
Published: (2024)

Learning Majority-to-Minority Transformations with MMD and Triplet Loss for Imbalanced Classification
by: Cha, Suman, et al.
Published: (2025)

Dimension-Free Decision Calibration for Nonlinear Loss Functions
by: Tang, Jingwu, et al.
Published: (2025)

Edge Contrastive Learning: An Augmentation-Free Graph Contrastive Learning Model
by: Li, Yujun, et al.
Published: (2024)