Diffusion-Models-Seminar

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Diffusion-Models-Seminar

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# Diffusion-Models-Seminar
### News
We are switching into an irregular meeting, where we discuss the recent literature or research problems concerning diffusion models (or sometimes generative modeling in general). If you want to join our group, please send your CV to ml.swlee@gmail.com.

|       Date       | Topic | Presenter | Summary | Video |
|:----------------:|:----------------------------------------:|:----------:|:------:|:------:
| 14th November, 2021 | [Denoising Diffusion Probabilistic Models](https://arxiv.org/abs/2006.11239) | Sangyun Lee | [Summary](https://sang-yun-lee.notion.site/Denoising-Diffusion-Probabilistic-Models-ade353a9abaa41d98c3ae2c18b52c129) | [Video](https://youtu.be/sNkVRr56MtI)
| 20th November, 2021 | [Improved Denoising Diffusion Probabilistic Models](https://arxiv.org/abs/2102.09672) | Junha Hyung | [Summary](https://sang-yun-lee.notion.site/Improved-Denoising-Diffusion-Probabilistic-Models-efa847335aef4163bfd3ee96c176f659) | [Video](https://youtu.be/8dchQOqvrCE)
| 20th November, 2021 | [Diffusion Models Beat GANs on Image Synthesis](https://arxiv.org/abs/2105.05233) | Sangyun Lee | [Summary](https://sang-yun-lee.notion.site/Diffusion-Models-Beat-GANs-on-Image-Synthesis-eb1f3826618d42e89d92e489c39f1371) | [Video](https://youtu.be/bSqA2AIaHy8)
| 28th November, 2021 | [ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models](https://arxiv.org/abs/2108.02938) | Youngin Cho | [Summary](https://sang-yun-lee.notion.site/ILVR-Conditioning-Method-for-Denoising-Diffusion-Probabilistic-Models-06e9b5aa7644448e931161351cb21cd8) | [Video](https://youtu.be/NKdueTNOrR0)
| 28th November, 2021 | [Deep Unsupervised Learning using Non equilibrium Thermodynamics](https://arxiv.org/abs/1503.03585) | Sejik Park | [Summary](https://sang-yun-lee.notion.site/Deep-Unsupervised-Learning-using-Non-equilibrium-Thermodynamics-6492cd4a916049569efb837d842c47f4) | [Video](https://youtu.be/Nr0j8ObDB7w)
| 05th December, 2021 | [SRDiff: Single Image Super-Resolution with Diffusion Probabilistic Models](https://arxiv.org/abs/2104.14951) | Sanghyeon Lee | [Summary](https://sang-yun-lee.notion.site/SRDiff-Single-Image-Super-Resolution-with-Diffusion-Probabilistic-Models-c00b88ebc2d4412a8a2b3a2801eaaadc) | [Video](https://youtu.be/Yuz5YyGa2iI)
| 12th December, 2021 | [Vector Quantized Diffusion Model for Text-to-Image Synthesis](https://arxiv.org/abs/2111.14822) | Jiyoung Lee | [Summary](https://sang-yun-lee.notion.site/Vector-Quantized-Diffusion-Model-for-Text-to-Image-Synthesis-7b9ebb43f14242c887af47b8a9b9b268) | [Video](https://youtu.be/LNvgRgyBs0M)
| 19th December, 2021 | [Score-based Generative Modelling through stochastic differential equations](https://arxiv.org/abs/2011.13456) | Hyungjin Chung | [Summary](https://sang-yun-lee.notion.site/Score-based-Generative-Modelling-through-stochastic-differential-equations-59ce3235b479415a82d79dc7e644285b) | [Video](https://youtu.be/yqF1IkdCQ4Y)
| 26th December, 2021 | [TACKLING THE GENERATIVE LEARNING TRILEMMA WITH DENOISING DIFFUSION GANS](https://arxiv.org/abs/2112.07804) | Sangyun Lee | [Summary](https://sang-yun-lee.notion.site/TACKLING-THE-GENERATIVE-LEARNING-TRILEMMA-WITH-DENOISING-DIFFUSION-GANS-cca24f847e4c4d57abfaee49f37cbbaa) | [Video](https://youtu.be/sta4xSVOI4E)
| 26th December, 2021 | [CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation](https://arxiv.org/abs/2107.03502) | Heejoon Koo | [Summary](https://sang-yun-lee.notion.site/CSDI-Conditional-Score-based-Diffusion-Models-for-Probabilistic-Time-Series-Imputation-ef04e8ffcc024b389d652f6b1972f667) 
| 2nd January, 2022 | [GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models](https://arxiv.org/abs/2112.10741) | Junha Hyung | [Summary](https://sang-yun-lee.notion.site/GLIDE-Towards-Photorealistic-Image-Generation-and-Editing-with-Text-Guided-Diffusion-Models-86036ea0bc344cd596a128f2de3fb9bb) | [Video](https://youtu.be/UefLZLbxM4g)
| 9th January, 2022 | [Denoising Diffusion Implicit Models](https://arxiv.org/abs/2010.02502) | Sejik Park | [Summary](https://www.notion.so/sang-yun-lee/Denoising-Diffusion-Implicit-Models-6cd7d42f65134996817594ffbce35488) | [Video](https://youtu.be/kGgO1ZPddwg)
| 9th January, 2022 | [HIGH FIDELITY VISUALIZATION OF WHAT YOUR SELF-SUPERVISED REPRESENTATION KNOWS ABOUT](https://arxiv.org/abs/2112.09164) | Jiyoung Lee | [Summary](https://www.notion.so/sang-yun-lee/HIGH-FIDELITY-VISUALIZATION-OF-WHAT-YOUR-SELF-SUPERVISED-REPRESENTATION-KNOWS-ABOUT-a9e7410a1c6f46a6850fcb8c08788ed7) | [Video](https://youtu.be/AOWs9Hb8r18)
| 16th January, 2022 | [Score-Based Generative Modeling with Critically-Damped Langevin Diffusion](https://arxiv.org/abs/2112.07068) | Hyungjin Chung | [Summary](https://sang-yun-lee.notion.site/Score-Based-Generative-Modeling-with-Critically-Damped-Langevin-Diffusion-1fb77e7099b94520a36d5b4372595b98) | [Video](https://youtu.be/_sGj5_8d3MY)
| 23rd January, 2022 | [Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting](https://arxiv.org/abs/2101.12072) | Heejoon Koo  | [Summary](https://sang-yun-lee.notion.site/Autoregressive-Denoising-Diffusion-Models-for-Multivariate-Probabilistic-Time-Series-Forecasting-IC-ee13c933c870476bbab3c975721e81ba) | [Video](https://youtu.be/KrKMErU4gRI)
| 30th January, 2022 | [Generative modeling by estimating gradients of the data distribution](https://arxiv.org/abs/1907.05600) | Chanwoo Park  | [Summary](https://www.notion.so/sang-yun-lee/Generative-modeling-by-estimating-gradients-of-the-data-distribution-cf9f8f0cba134c3f95c4dbf42e37e59a) | [Video](https://youtu.be/N2cSb9aW9aU)
| 6th February, 2022 | [Variational Diffusion Models](https://arxiv.org/abs/2107.00630) | Sangyun Lee | [Summary](https://www.notion.so/sang-yun-lee/Variational-Diffusion-Models-f72d9cb1a2004a9088470c95cdc929e3) | [Video](https://youtu.be/yR81b3UxgaI)
| 13th February, 2022 | [Denoising Diffusion Restoration Models](https://arxiv.org/abs/2201.11793) | Gwanghyun Kim | [Summary](https://sang-yun-lee.notion.site/Denoising-Diffusion-Restoration-Models-DDRM-275e61cfcf7843ffb0cbdbeaa572846a) | [Video](https://youtu.be/ZbB__c7pi40)
| 13th February, 2022 | [Diffusion Normalizing Flow](https://arxiv.org/abs/2110.07579) | Sejik Park | [Summary](https://sang-yun-lee.notion.site/Diffusion-Normalizing-Flow-5c8eff4fba024a28b0b95c043cb1ff8c) | [Video](https://youtu.be/vB6dsUtWwz0)
| 20th February, 2022 | [Score-based generative modeling in latent space](https://arxiv.org/abs/2106.05931) | Hyungjin Chung | [Summary](https://sang-yun-lee.notion.site/Score-based-generative-modeling-in-latent-space-6c08ad787289403095b7b9e51421724c) | [Video](https://youtu.be/ssxPHItnkqc)
| 27th February, 2022 | [Blended Diffusion for Text-driven Editing of Natural Images](https://arxiv.org/abs/2111.14818) | Heejook Koo | [Summary](https://sang-yun-lee.notion.site/Blended-Diffusion-for-Text-driven-Editing-of-Natural-Images-arXiv-2022-a893aa19a652446692f58fe2907c0ca2) | [Video](https://youtu.be/i1k63kb4i-s)
| 6th March, 2022 | [Score based Generative Modeling of Graphs via the system of Stochastic Differential Equations](https://arxiv.org/abs/2202.02514) | Chanwoo Park | [Summary](https://sang-yun-lee.notion.site/Score-based-Generative-Modeling-of-Graphs-via-the-system-of-Stochastic-Differential-Equations-GDSS-13a24ac8fefc480cbf831f48ccffa0ff) | [Video](https://youtu.be/VU-aB2j2rT8)
| 13th March, 2022 | [High-Resolution Image Synthesis with Latent Diffusion Models ](https://arxiv.org/abs/2112.10752) | Sangyun Lee | [Summary](https://sang-yun-lee.notion.site/High-Resolution-Image-Synthesis-with-Latent-Diffusion-Models-a136345c8edb4b048b02b89716d105b5) | [Video](https://youtu.be/ibB6aR9xA1Q)
| 20th March, 2022 | [Score-Based Point Cloud Denoising](https://arxiv.org/abs/2107.10981) | Jinhwan Seok | [Summary](https://sang-yun-lee.notion.site/Score-Based-Point-Cloud-Denoising-28be8c50cd2e46809c4aec3046b3b61d) | [Video](https://youtu.be/ppmAgu3oHqU)
| 27th March, 2022 | [DiffusionCLIP: Text-Guided Diffusion Models for Robust Image Manipulation](https://arxiv.org/abs/2110.02711) | Gwanghyun Kim | [Summary](https://www.notion.so/sang-yun-lee/DiffusionCLIP-Text-Guided-Diffusion-Models-for-Robust-Image-Manipulation-a70cf218c6a54ef29cf91d7047fe7b34) | [Video](https://youtu.be/cmbul5-o_cQ)
| 3rd April, 2022 | [Structured Denoising Diffusion Models in Discrete State-Spaces](https://arxiv.org/abs/2107.03006) | Hyungjin Chung | [Summary](https://www.notion.so/sang-yun-lee/Structured-Denoising-Diffusion-Models-in-Discrete-State-Spaces-6bbe59d310b545f0a4ed01e06bee2f18) | [Video](https://youtu.be/SaZJ2cZ6FZI)
| 17th April, 2022 | Recent Trends In Diffusion-Based Text-Conditional Image Synthesis | Sangyun Lee | [Summary](https://www.notion.so/sang-yun-lee/Recent-Trends-In-Diffusion-Based-Text-Conditional-Image-Synthesis-cd39f012f76049d4930b7c96f8a9655e) <br /> [Summary (English)](https://sangyun884.github.io/recent-trends-in-diffusion-based-text-conditional/) | [Video](https://youtu.be/Riy0Cnsorhk)
| 8th May, 2022 | [Solving Inverse Problems in Medical Imaging with Score-Based Generative Models](https://arxiv.org/abs/2111.08005) | Hyungjin Chung |  | [Video](https://youtu.be/jFE-aLW1wZA)
| 22nd May, 2022 | Derivation of Probabilistic Flow ODE / Kolmogorov forward equation (Fokker Planck equation) | Sangyun Lee |  [Summary](https://sang-yun-lee.notion.site/Derivation-of-Probabilistic-Flow-ODE-Kolmogorov-forward-equation-Fokker-Planck-equation-d5d2462c01ee44da8d2484215b697ef5)  | [Video](https://youtu.be/lA7T5d_4WcE)
| 22nd May, 2022 | [Retreival-Augmented Diffusion model](https://arxiv.org/abs/2204.11824) | Sungho Park |  [Summary](https://naem1023.github.io/generative-model/nlp/Retrieval-Augmented-Diffusion-model/)  | [Video](https://youtu.be/_b3cMfvx4xs)
| 29th May, 2022 | [Generating High Fidelity Data from Low-density Regions using Diffusion Models](https://arxiv.org/abs/2203.17260) | Gwanghyun Kim |  [Summary](https://sang-yun-lee.notion.site/Generating-High-Fidelity-Data-from-Low-density-Regions-using-Diffusion-Models-c357143a9d334fc184eaf7ff2952cbe6)  | [Video](https://youtu.be/S-oY-EnMSwg)
| 5th June, 2022 | Diffusion Models for Video | Hyungjin Chung |  [Summary](https://sang-yun-lee.notion.site/Diffusion-Models-for-Video-75454f86076a4285944240f1b993950d)  | [Video](https://youtu.be/CqCNLH4ZRDo)
| 10th July, 2022 | Diffusion Autoencoders: Toward a Meaningful and Decodable Representation | Gwanghyun Kim |  [Summary](https://sang-yun-lee.notion.site/Diffusion-Autoencoders-Toward-a-Meaningful-and-Decodable-Representation-1334f11d29d5446fbd689174f4c70fde)  | [Video](https://youtu.be/Af9NK82INJo)
| 17th July, 2022 | Elucidating the Design Space of Diffusion-Based Generative Models | Hyungjin Chung |  [Summary](https://sang-yun-lee.notion.site/Elucidating-the-Design-Space-of-Diffusion-Based-Generative-Models-a81b14bf297743ec90a72c11f0fbce57)  | [Video](https://youtu.be/FSSAieHkX88)
| 31st July, 2022 | Estimating High Order Gradients of the Data Distribution by Denoising | Sangyun Lee |  [Summary](https://www.notion.so/sang-yun-lee/Estimating-High-Order-Gradients-of-the-Data-Distribution-by-Denoising-94688d76461544bab6f18173ed3536e6)  | 
| 25th September, 2022 | Improving Diffusion Models for Inverse Problems using Manifold Constraints | Hyungjin Chung |  [Summary](https://www.notion.so/sang-yun-lee/Improving-Diffusion-Models-for-Inverse-Problems-using-Manifold-Constraints-01e82afda989428e8b5faad1c3bbebf2)  | [Video](https://youtu.be/mjfinYDJTMc)

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