index - Byung-Hak (Hak) Kim, 김병학

MyEar: LLM-Powered Agentic AI for Personalized Spending Narratives

SCRIPTy: Story & Content Review Intelligence Platform

NexusSum: Hierarchical LLM Agents for Long-Form Narrative Summarization

DIAMOND: An LLM-Driven Agent for Context-Aware Baseball Highlight Summarization

Agent-as-Judge for Factual Summarization of Long Narratives

CREFT: Sequential Multi-Agent LLM for Character Relation Extraction

Addressing Baumol’s Cost Disease in Healthcare with Machine Learning

Deep Claim: Payer Response Prediction from Claims Data with Deep Learning

Read, Attend, and Code: Pushing the Limits of Medical Codes Prediction from Clinical Notes by Machines

Can Current Explainability Help Provide References in Clinical Notes to Support Humans Annotate Medical Codes?

Medical Codes Prediction from Clinical Notes: From Human Coders to Machines

RegCLR: A Self-Supervised Framework for Tabular Representation Learning in the Wild

Multimodal Representation Learning of Cardiovascular Magnetic Resonance Imaging

Reducing Contextual Bias in Cardiac Magnetic Resonance Imaging Deep Learning Using Contrastive Self-Supervision

Clinical NLP Workshop at NAACL 2022

ML4H: Machine Learning for Health 2021

ICCV 2021 Workshop on Computer Vision for Automated Medical Diagnosis

ICML 2021 Workshop on Self-Supervised Learning for Reasoning and Perception

NeurIPS 2019 Workshop on Fair ML for Health

SummDiff: Generative Modeling of Video Summarization with Diffusion

Deep Learning-Based Telephony Speech Recognition in the Wild

LumièreNet: Lecture Video Synthesis from Audio

Deep Learning to Predict Student Outcomes

Deep Learning to help student’s Deep Learning

GritNet: Student Performance Prediction with Deep Learning

KDD 2019 Workshop on Deep Learning for Education (DL4E)

Joint Decoding of LDPC Codes and Finite-State Channels via Linear-Programming

An Iterative Joint Linear-Programming Decoding of LDPC Codes and Finite-State Channels

On the Joint Decoding of LDPC Codes and Finite-State Channels via Linear-Programming

IMP: A Message-Passing Algorithm for Matrix Completion

Message-Passing Inference on a Factor Graph for Collaborative Filtering

GenAI 2.0: A Landscape for Silicon Valley Startups

Moving Forward with Machine Learning Startups!

Press

Books

ML Paper Reading Group

Data Intelligence Podcast

의료 인공지능 & 디지털 헬스

실험실 밖으로 나온 인공지능

데이터 과학자의 학습법 #1

데이터 과학자의 학습법 #2

Byung-Hak KIM

MyEar: LLM-Powered Agentic AI for Personalized Spending Narratives

SCRIPTy: Story & Content Review Intelligence Platform

NexusSum: Hierarchical LLM Agents for Long-Form Narrative Summarization

DIAMOND: An LLM-Driven Agent for Context-Aware Baseball Highlight Summarization

Agent-as-Judge for Factual Summarization of Long Narratives

CREFT: Sequential Multi-Agent LLM for Character Relation Extraction

Addressing Baumol’s Cost Disease in Healthcare with Machine Learning

Deep Claim: Payer Response Prediction from Claims Data with Deep Learning

Read, Attend, and Code: Pushing the Limits of Medical Codes Prediction from Clinical Notes by Machines

Can Current Explainability Help Provide References in Clinical Notes to Support Humans Annotate Medical Codes?

Medical Codes Prediction from Clinical Notes: From Human Coders to Machines

RegCLR: A Self-Supervised Framework for Tabular Representation Learning in the Wild

Multimodal Representation Learning of Cardiovascular Magnetic Resonance Imaging

Reducing Contextual Bias in Cardiac Magnetic Resonance Imaging Deep Learning Using Contrastive Self-Supervision

Clinical NLP Workshop at NAACL 2022

ML4H: Machine Learning for Health 2021

ICCV 2021 Workshop on Computer Vision for Automated Medical Diagnosis

ICML 2021 Workshop on Self-Supervised Learning for Reasoning and Perception

NeurIPS 2019 Workshop on Fair ML for Health

SummDiff: Generative Modeling of Video Summarization with Diffusion

Deep Learning-Based Telephony Speech Recognition in the Wild

LumièreNet: Lecture Video Synthesis from Audio

Deep Learning to Predict Student Outcomes

Deep Learning to help student’s Deep Learning

GritNet: Student Performance Prediction with Deep Learning

KDD 2019 Workshop on Deep Learning for Education (DL4E)

Joint Decoding of LDPC Codes and Finite-State Channels via Linear-Programming