Jungmook Kang https://mookjsi.github.io/ Recent content on Jungmook Kang Hugo -- 0.168.0 en Thu, 03 Sep 2026 00:00:00 +0000 Diffusion Model and Its Applications https://mookjsi.github.io/posts/diffusion2/ Thu, 03 Sep 2026 00:00:00 +0000 https://mookjsi.github.io/posts/diffusion2/ StatLet seminar 09/04 TimeFormer: Capturing Temporal Relationships of Deformable 3D Gaussians for Robust Reconstruction https://mookjsi.github.io/posts/paper-review-timeformer/ Mon, 01 Dec 2025 00:00:00 +0000 https://mookjsi.github.io/posts/paper-review-timeformer/ YBIGTA 12/01 DS Session Presentation Diffusion Models: From VAEs to DDPM Derivation https://mookjsi.github.io/posts/diffusion/ Tue, 25 Nov 2025 00:00:00 +0000 https://mookjsi.github.io/posts/diffusion/ A presentation I gave at a YBIGTA. Mathematical derivation of DGM Flamingo: a Visual Language Model for Few-Shot Learning https://mookjsi.github.io/posts/paper-review-flamingo/ Tue, 25 Nov 2025 00:00:00 +0000 https://mookjsi.github.io/posts/paper-review-flamingo/ YBIGTA DS Session 11/25 Presentation Generative Adversarial Nets (GAN) 논문 리뷰 https://mookjsi.github.io/posts/paper-review-gan/ Tue, 11 Nov 2025 00:00:00 +0000 https://mookjsi.github.io/posts/paper-review-gan/ YBIGTA DS Session 11/11 Presentation SimCLR 논문 리뷰 https://mookjsi.github.io/posts/paper-review-simclr/ Tue, 28 Oct 2025 00:00:00 +0000 https://mookjsi.github.io/posts/paper-review-simclr/ YBIGTA 10/28 DS Session Presentation Segment Anything 논문 리뷰 https://mookjsi.github.io/posts/paper-review-sam/ Tue, 30 Sep 2025 00:00:00 +0000 https://mookjsi.github.io/posts/paper-review-sam/ YBIGTA DS Session 09/10 Presentation DETR: End-to-End Object Detection with Transformers https://mookjsi.github.io/posts/paper-review-detr/ Tue, 23 Sep 2025 00:00:00 +0000 https://mookjsi.github.io/posts/paper-review-detr/ YBIGTA DS 09/23 Session Presentation ResNet - 더 깊은 신경망을 위한 잔차 학습 https://mookjsi.github.io/posts/paper-review-resnet/ Tue, 16 Sep 2025 00:00:00 +0000 https://mookjsi.github.io/posts/paper-review-resnet/ YBIGTA 09/16 DS Session Presentation Advanced Policy Gradient Methods: TRPO & PPO https://mookjsi.github.io/posts/trpoppo/ Tue, 26 Aug 2025 00:00:00 +0000 https://mookjsi.github.io/posts/trpoppo/ YBIGTA 08/25 Summer Session Presentation Promptriever - Instruction-Trained Retrievers https://mookjsi.github.io/posts/paper-review-promptriever/ Thu, 12 Jun 2025 00:00:00 +0000 https://mookjsi.github.io/posts/paper-review-promptriever/ 06/12 ITML Lab Meeting Simplifying Neural Nets by Discovering Flat Minima https://mookjsi.github.io/posts/paper-review-flatminima/ Thu, 15 May 2025 00:00:00 +0000 https://mookjsi.github.io/posts/paper-review-flatminima/ 05/15 ITML Lab meeting Max-Margin Token Selection in Attention Mechanism https://mookjsi.github.io/posts/paper-review-maxtoken/ Wed, 30 Apr 2025 00:00:00 +0000 https://mookjsi.github.io/posts/paper-review-maxtoken/ 04/30 ITML Lab Meeting Transformer: Attention부터 BERT까지 https://mookjsi.github.io/posts/transformer/ Tue, 01 Apr 2025 00:00:00 +0000 https://mookjsi.github.io/posts/transformer/ YBIGTA 04/01 DS Session Presentation. Attention, Transformer, and BERT step-by-step. Stochastic Approximation to Contrastive Learning https://mookjsi.github.io/posts/paper-review-stochastic/ Wed, 05 Mar 2025 00:00:00 +0000 https://mookjsi.github.io/posts/paper-review-stochastic/ ICLR 2025 Paper Review When to Retrieve? https://mookjsi.github.io/posts/paper-review-whentoretrieve/ Fri, 28 Feb 2025 00:00:00 +0000 https://mookjsi.github.io/posts/paper-review-whentoretrieve/ ACL 2024 Paper Review About Me https://mookjsi.github.io/about/ Mon, 01 Jan 0001 00:00:00 +0000 https://mookjsi.github.io/about/ <h2 id="education">Education</h2> <ul> <li> <p><strong>Seoul National University</strong>, Seoul, Korea (Mar 2026 -)</p> <ul> <li>M.S in Statistics</li> </ul> </li> <li> <p><strong>Yonsei University</strong>, Seoul, Korea (Mar 2022 - Feb 2026)</p> <ul> <li>B.A in Applied Statistics</li> </ul> </li> </ul> <hr> <h2 id="research-interests">Research Interests</h2> <ul> <li>Machine Learning</li> <li>High Dimensional Data Analysis</li> </ul>