default search action
Taesup Moon
Person information
SPARQL queries
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2025
- [j18]Taeeon Park, Sangwon Jung, Sanghyuk Chun, Taesup Moon:
FairDRO: Group fairness regularization via classwise robust optimization. Neural Networks 182: 106891 (2025) - 2024
- [j17]Sunghwan Joo, Taesup Moon:
Debiased Learning via Composed Conceptual Sensitivity Regularization. IEEE Access 12: 170295-170308 (2024) - [c43]Sungmin Cha, Sungjun Cho, Dasol Hwang, Honglak Lee, Taesup Moon, Moontae Lee:
Learning to Unlearn: Instance-Wise Unlearning for Pre-trained Classifiers. AAAI 2024: 11186-11194 - [c42]Jaeseok Byun, Dohoon Kim, Taesup Moon:
MAFA: Managing False Negatives for Vision-Language Pre-Training. CVPR 2024: 27304-27314 - [c41]Donggyu Lee, Sangwon Jung, Taesup Moon:
Continual Learning in the Presence of Spurious Correlations: Analyses and a Simple Baseline. ICLR 2024 - [c40]Sungmin Cha, Kyunghyun Cho, Taesup Moon:
Regularizing with Pseudo-Negatives for Continual Self-Supervised Learning. ICML 2024 - [c39]Heewoong Choi, Sangwon Jung, Hongjoon Ahn, Taesup Moon:
Listwise Reward Estimation for Offline Preference-based Reinforcement Learning. ICML 2024 - [c38]Sungmin Cha, Naeun Ko, Heewoong Choi, Youngjoon Yoo, Taesup Moon:
NCIS: Neural Contextual Iterative Smoothing for Purifying Adversarial Perturbations. WACV 2024: 3777-3787 - [i44]Hongjoon Ahn, Jinu Hyeon, Youngmin Oh, Bosun Hwang, Taesup Moon:
Reset & Distill: A Recipe for Overcoming Negative Transfer in Continual Reinforcement Learning. CoRR abs/2403.05066 (2024) - [i43]Jihwan Kwak, Sungmin Cha, Taesup Moon:
Towards Realistic Incremental Scenario in Class Incremental Semantic Segmentation. CoRR abs/2405.09858 (2024) - [i42]Jaeseok Byun, Seokhyeon Jeong, Wonjae Kim, Sanghyuk Chun, Taesup Moon:
Reducing Task Discrepancy of Text Encoders for Zero-Shot Composed Image Retrieval. CoRR abs/2406.09188 (2024) - [i41]Heewoong Choi, Sangwon Jung, Hongjoon Ahn, Taesup Moon:
Listwise Reward Estimation for Offline Preference-based Reinforcement Learning. CoRR abs/2408.04190 (2024) - 2023
- [j16]Joonhyun Jeong, Sungmin Cha, Jongwon Choi, Sangdoo Yun, Taesup Moon, Youngjoon Yoo:
Observations on K-Image Expansion of Image-Mixing Augmentation. IEEE Access 11: 16631-16643 (2023) - [c37]Donggyu Lee, Sangwon Jung, Taesup Moon:
Issues for Continual Learning in the Presence of Dataset Bias. AAAI Bridge Program 2023: 92-99 - [c36]Sunghwan Joo, Seokhyeon Jeong, Juyeon Heo, Adrian Weller, Taesup Moon:
Towards More Robust Interpretation via Local Gradient Alignment. AAAI 2023: 8168-8176 - [c35]Sungmin Cha, Sungjun Cho, Dasol Hwang, Sunwon Hong, Moontae Lee, Taesup Moon:
Rebalancing Batch Normalization for Exemplar-Based Class-Incremental Learning. CVPR 2023: 20127-20136 - [c34]Sangwon Jung, Taeeon Park, Sanghyuk Chun, Taesup Moon:
Re-weighting Based Group Fairness Regularization via Classwise Robust Optimization. ICLR 2023 - [c33]Peter Yongho Kim, Junbeom Kwon, Sunghwan Joo, Sangyoon Bae, Donggyu Lee, Yoonho Jung, Shinjae Yoo, Jiook Cha, Taesup Moon:
SwiFT: Swin 4D fMRI Transformer. NeurIPS 2023 - [i40]Sungmin Cha, Sungjun Cho, Dasol Hwang, Honglak Lee, Taesup Moon, Moontae Lee:
Learning to Unlearn: Instance-wise Unlearning for Pre-trained Classifiers. CoRR abs/2301.11578 (2023) - [i39]Sangwon Jung, Taeeon Park, Sanghyuk Chun, Taesup Moon:
Re-weighting Based Group Fairness Regularization via Classwise Robust Optimization. CoRR abs/2303.00442 (2023) - [i38]Donggyu Lee, Sangwon Jung, Taesup Moon:
Continual Learning in the Presence of Spurious Correlation. CoRR abs/2303.11863 (2023) - [i37]Sungmin Cha, Taesup Moon:
Sy-CON: Symmetric Contrastive Loss for Continual Self-Supervised Representation Learning. CoRR abs/2306.05101 (2023) - [i36]Peter Yongho Kim, Junbeom Kwon, Sunghwan Joo, Sangyoon Bae, Donggyu Lee, Yoonho Jung, Shinjae Yoo, Jiook Cha, Taesup Moon:
SwiFT: Swin 4D fMRI Transformer. CoRR abs/2307.05916 (2023) - [i35]Juhyeon Park, Seokhyeon Jeong, Taesup Moon:
TLDR: Text Based Last-layer Retraining for Debiasing Image Classifiers. CoRR abs/2311.18291 (2023) - [i34]Jaeseok Byun, Dohoon Kim, Taesup Moon:
Converting and Smoothing False Negatives for Vision-Language Pre-training. CoRR abs/2312.06112 (2023) - 2022
- [j15]Taeeon Park, Jihwan Kwak, Hongjoon Ahn, Jinwoong Lee, Jaehyuk Lim, Sangho Yu, Changhwan Shin, Taesup Moon:
GAN-Based Framework for Unified Estimation of Process-Induced Random Variation in FinFET. IEEE Access 10: 130001-130023 (2022) - [j14]Donggyu Lee, Hyeongmin Park, Taesup Moon, Youngwook Kim:
Continual Learning of Micro-Doppler Signature-Based Human Activity Classification. IEEE Geosci. Remote. Sens. Lett. 19: 1-5 (2022) - [c32]Sangwon Jung, Sanghyuk Chun, Taesup Moon:
Learning Fair Classifiers with Partially Annotated Group Labels. CVPR 2022: 10338-10347 - [c31]Jaeseok Byun, Taebaek Hwang, Jianlong Fu, Taesup Moon:
GRIT-VLP: Grouped Mini-batch Sampling for Efficient Vision and Language Pre-training. ECCV (19) 2022: 395-412 - [c30]Hongjoon Ahn, Yongyi Yang, Quan Gan, Taesup Moon, David P. Wipf:
Descent Steps of a Relation-Aware Energy Produce Heterogeneous Graph Neural Networks. NeurIPS 2022 - [e1]Andreas Holzinger, Randy Goebel, Ruth Fong, Taesup Moon, Klaus-Robert Müller, Wojciech Samek:
xxAI - Beyond Explainable AI - International Workshop, Held in Conjunction with ICML 2020, July 18, 2020, Vienna, Austria, Revised and Extended Papers. Lecture Notes in Computer Science 13200, Springer 2022, ISBN 978-3-031-04082-5 [contents] - [i33]Sungmin Cha, Soonwon Hong, Moontae Lee, Taesup Moon:
Task-Balanced Batch Normalization for Exemplar-based Class-Incremental Learning. CoRR abs/2201.12559 (2022) - [i32]Sungmin Cha, Dongsub Shim, Hyunwoo Kim, Moontae Lee, Honglak Lee, Taesup Moon:
Is Continual Learning Truly Learning Representations Continually? CoRR abs/2206.08101 (2022) - [i31]Hongjoon Ahn, Yongyi Yang, Quan Gan, David Wipf, Taesup Moon:
Descent Steps of a Relation-Aware Energy Produce Heterogeneous Graph Neural Networks. CoRR abs/2206.11081 (2022) - [i30]Jaeseok Byun, Taebaek Hwang, Jianlong Fu, Taesup Moon:
GRIT-VLP: Grouped Mini-batch Sampling for Efficient Vision and Language Pre-training. CoRR abs/2208.04060 (2022) - [i29]Sunghwan Joo, Seokhyeon Jeong, Juyeon Heo, Adrian Weller, Taesup Moon:
Towards More Robust Interpretation via Local Gradient Alignment. CoRR abs/2211.15900 (2022) - 2021
- [j13]Yong Sung Kil, Jun Min Song, Sang-Hyo Kim, Taesup Moon, Seok-Ho Chang:
Deep Learning Aided Blind Synchronization Word Estimation. IEEE Access 9: 30321-30334 (2021) - [c29]Jaeseok Byun, Sungmin Cha, Taesup Moon:
FBI-Denoiser: Fast Blind Image Denoiser for Poisson-Gaussian Noise. CVPR 2021: 5768-5777 - [c28]Sangwon Jung, Donggyu Lee, Taeeon Park, Taesup Moon:
Fair Feature Distillation for Visual Recognition. CVPR 2021: 12115-12124 - [c27]Hongjoon Ahn, Jihwan Kwak, Subin Lim, Hyeonsu Bang, Hyojun Kim, Taesup Moon:
SS-IL: Separated Softmax for Incremental Learning. ICCV 2021: 824-833 - [c26]Sungmin Cha, Hsiang Hsu, Taebaek Hwang, Flávio P. Calmon, Taesup Moon:
CPR: Classifier-Projection Regularization for Continual Learning. ICLR 2021 - [c25]Sungmin Cha, Taeeon Park, Byeongjoon Kim, Jongduk Baek, Taesup Moon:
GAN2GAN: Generative Noise Learning for Blind Denoising with Single Noisy Images. ICLR 2021 - [c24]Sungmin Cha, Beomyoung Kim, Youngjoon Yoo, Taesup Moon:
SSUL: Semantic Segmentation with Unknown Label for Exemplar-based Class-Incremental Learning. NeurIPS 2021: 10919-10930 - [i28]Jaeseok Byun, Sungmin Cha, Taesup Moon:
FBI-Denoiser: Fast Blind Image Denoiser for Poisson-Gaussian Noise. CoRR abs/2105.10967 (2021) - [i27]Sangwon Jung, Donggyu Lee, Taeeon Park, Taesup Moon:
Fair Feature Distillation for Visual Recognition. CoRR abs/2106.04411 (2021) - [i26]Sungmin Cha, Beomyoung Kim, Youngjoon Yoo, Taesup Moon:
SSUL: Semantic Segmentation with Unknown Label for Exemplar-based Class-Incremental Learning. CoRR abs/2106.11562 (2021) - [i25]Sungmin Cha, Naeun Ko, Youngjoon Yoo, Taesup Moon:
Self-Supervised Iterative Contextual Smoothing for Efficient Adversarial Defense against Gray- and Black-Box Attack. CoRR abs/2106.11644 (2021) - [i24]Joonhyun Jeong, Sungmin Cha, Youngjoon Yoo, Sangdoo Yun, Taesup Moon, Jongwon Choi:
Observations on K-image Expansion of Image-Mixing Augmentation for Classification. CoRR abs/2110.04248 (2021) - [i23]Sungmin Cha, Seonwoo Min, Sungroh Yoon, Taesup Moon:
Supervised Neural Discrete Universal Denoiser for Adaptive Denoising. CoRR abs/2111.12350 (2021) - [i22]Sangwon Jung, Sanghyuk Chun, Taesup Moon:
Learning Fair Classifiers with Partially Annotated Group Labels. CoRR abs/2111.14581 (2021) - 2020
- [j12]Jaeseok Byun, Taesup Moon:
Learning Blind Pixelwise Affine Image Denoiser With Single Noisy Images. IEEE Signal Process. Lett. 27: 1105-1109 (2020) - [c23]Taeeon Park, Taesup Moon:
Unsupervised Neural Universal Denoiser for Finite-Input General-Output Noisy Channel. AISTATS 2020: 331-340 - [c22]Andreas Holzinger, Randy Goebel, Ruth Fong, Taesup Moon, Klaus-Robert Müller, Wojciech Samek:
xxAI - Beyond Explainable Artificial Intelligence. xxAI@ICML 2020: 3-10 - [c21]Sangwon Jung, Hongjoon Ahn, Sungmin Cha, Taesup Moon:
Continual Learning with Node-Importance based Adaptive Group Sparse Regularization. NeurIPS 2020 - [c20]Hongjoon Ahn, Taesup Moon:
Iterative Channel Estimation for Discrete Denoising under Channel Uncertainty. UAI 2020: 91-100 - [i21]Taeeon Park, Taesup Moon:
Unsupervised Neural Universal Denoiser for Finite-Input General-Output Noisy Channel. CoRR abs/2003.02623 (2020) - [i20]Sangwon Jung, Hongjoon Ahn, Sungmin Cha, Taesup Moon:
Adaptive Group Sparse Regularization for Continual Learning. CoRR abs/2003.13726 (2020) - [i19]Hongjoon Ahn, Taesup Moon:
A Simple Class Decision Balancing for Incremental Learning. CoRR abs/2003.13947 (2020) - [i18]Sungmin Cha, Hsiang Hsu, Flávio P. Calmon, Taesup Moon:
CPR: Classifier-Projection Regularization for Continual Learning. CoRR abs/2006.07326 (2020)
2010 – 2019
- 2019
- [j11]Toan Duc Bui, Jitae Shin, Taesup Moon:
Skip-connected 3D DenseNet for volumetric infant brain MRI segmentation. Biomed. Signal Process. Control. 54 (2019) - [c19]Changho Shin, Sunghwan Joo, Jaeryun Yim, Hyoseop Lee, Taesup Moon, Wonjong Rhee:
Subtask Gated Networks for Non-Intrusive Load Monitoring. AAAI 2019: 1150-1157 - [c18]Sunghwan Joo, Sungmin Cha, Taesup Moon:
DoPAMINE: Double-Sided Masked CNN for Pixel Adaptive Multiplicative Noise Despeckling. AAAI 2019: 4031-4038 - [c17]Sungmin Cha, Taesup Moon:
Fully Convolutional Pixel Adaptive Image Denoiser. ICCV 2019: 4159-4168 - [c16]Juyeon Heo, Sunghwan Joo, Taesup Moon:
Fooling Neural Network Interpretations via Adversarial Model Manipulation. NeurIPS 2019: 2921-2932 - [c15]Hongjoon Ahn, Sungmin Cha, Donggyu Lee, Taesup Moon:
Uncertainty-based Continual Learning with Adaptive Regularization. NeurIPS 2019: 4394-4404 - [c14]Yongbee Park, Taesup Moon:
Working Vacation Scheduling of MX/M/1/N System using Neural Network. RiTA 2019: 20-25 - [i17]Juyeon Heo, Sunghwan Joo, Taesup Moon:
Fooling Neural Network Interpretations via Adversarial Model Manipulation. CoRR abs/1902.02041 (2019) - [i16]Sunghwan Joo, Sungmin Cha, Taesup Moon:
DoPAMINE: Double-sided Masked CNN for Pixel Adaptive Multiplicative Noise Despeckling. CoRR abs/1902.02530 (2019) - [i15]Hongjoon Ahn, Taesup Moon:
Iterative Channel Estimation for Discrete Denoising under Channel Uncertainty. CoRR abs/1902.08921 (2019) - [i14]Sungmin Cha, Taeeon Park, Taesup Moon:
GAN2GAN: Generative Noise Learning for Blind Image Denoising with Single Noisy Images. CoRR abs/1905.10488 (2019) - [i13]Hongjoon Ahn, Donggyu Lee, Sungmin Cha, Taesup Moon:
Uncertainty-based Continual Learning with Adaptive Regularization. CoRR abs/1905.11614 (2019) - 2018
- [c13]Sungmin Cha, Taesup Moon:
Neural Adaptive Image Denoiser. ICASSP 2018: 2981-2985 - [c12]Sungmin Cha, Taesup Moon:
UDLR Convolutional Network for Adaptive Image Denoiser. RiTA 2018: 55-61 - [i12]Sungmin Cha, Taesup Moon:
Fully Convolutional Pixel Adaptive Image Denoiser. CoRR abs/1807.07569 (2018) - [i11]Changho Shin, Sunghwan Joo, Jaeryun Yim, Hyoseop Lee, Taesup Moon, Wonjong Rhee:
Subtask Gated Networks for Non-Intrusive Load Monitoring. CoRR abs/1811.06692 (2018) - 2017
- [i10]Toan Duc Bui, Jitae Shin, Taesup Moon:
3D Densely Convolutional Networks for Volumetric Segmentation. CoRR abs/1709.03199 (2017) - [i9]Taesup Moon:
Uniform Concentration of the Loss Estimator for Neural DUDE. CoRR abs/1709.03657 (2017) - [i8]Sungmin Cha, Taesup Moon:
Neural Affine Grayscale Image Denoising. CoRR abs/1709.05672 (2017) - 2016
- [j10]Taehoon Lee, Taesup Moon, Seung Jean Kim, Sungroh Yoon:
Regularization and Kernelization of the Maximin Correlation Approach. IEEE Access 4: 1385-1392 (2016) - [j9]Youngwook Kim, Taesup Moon:
Human Detection and Activity Classification Based on Micro-Doppler Signatures Using Deep Convolutional Neural Networks. IEEE Geosci. Remote. Sens. Lett. 13(1): 8-12 (2016) - [j8]Jinhee Park, Rios Jesus Javier, Taesup Moon, Youngwook Kim:
Micro-Doppler Based Classification of Human Aquatic Activities via Transfer Learning of Convolutional Neural Networks. Sensors 16(12): 1990 (2016) - [c11]Taesup Moon, Seonwoo Min, Byunghan Lee, Sungroh Yoon:
Neural Universal Discrete Denoiser. NIPS 2016: 4772-4780 - [i7]Taesup Moon, Seonwoo Min:
Neural Universal Discrete Denoiser. CoRR abs/1605.07779 (2016) - 2015
- [j7]Taesup Moon, Yueqing Wang, Yang Liu, Bin Yu:
Evaluation of a MISR-Based High-Resolution Aerosol Retrieval Method Using AERONET DRAGON Campaign Data. IEEE Trans. Geosci. Remote. Sens. 53(8): 4328-4339 (2015) - [c10]Taesup Moon, Heeyoul Choi, Hoshik Lee, Inchul Song:
RNNDROP: A novel dropout for RNNS in ASR. ASRU 2015: 65-70 - [i6]Taehoon Lee, Taesup Moon, Seung Jean Kim, Sungroh Yoon:
Regularization and Kernelization of the Maximin Correlation Approach. CoRR abs/1502.06105 (2015) - [i5]Byunghan Lee, Taesup Moon, Sungroh Yoon, Tsachy Weissman:
DUDE-Seq: Fast Universal Denoising of Nucleotide Sequences. CoRR abs/1511.04836 (2015) - 2014
- [j6]Jiang Bian, Bo Long, Lihong Li, Taesup Moon, Anlei Dong, Yi Chang:
Exploiting User Preference for Online Learning in Web Content Optimization Systems. ACM Trans. Intell. Syst. Technol. 5(2): 33:1-33:23 (2014) - 2012
- [j5]Taesup Moon, Wei Chu, Lihong Li, Zhaohui Zheng, Yi Chang:
An Online Learning Framework for Refining Recency Search Results with User Click Feedback. ACM Trans. Inf. Syst. 30(4): 20:1-20:28 (2012) - [j4]Taesup Moon:
Universal Switching FIR Filtering. IEEE Trans. Signal Process. 60(3): 1460-1464 (2012) - [c9]Lihong Li, Wei Chu, John Langford, Taesup Moon, Xuanhui Wang:
Bandits with Generalized Linear Models. ICML On-line Trading of Exploration and Exploitation 2012: 19-36 - 2011
- [c8]Taesup Moon, Tsachy Weissman, Jae-Young Kim:
Discrete denoising of heterogeneous two-dimensional data. ISIT 2011: 1041-1045 - [c7]Yuanhua Lv, Taesup Moon, Pranam Kolari, Zhaohui Zheng, Xuanhui Wang, Yi Chang:
Learning to model relatedness for news recommendation. WWW 2011: 57-66 - [i4]Taesup Moon, Wei Chu, Lihong Li, Zhaohui Zheng, Yi Chang:
Refining Recency Search Results with User Click Feedback. CoRR abs/1103.3735 (2011) - 2010
- [c6]Taesup Moon, Georges Dupret, Shihao Ji, Ciya Liao, Zhaohui Zheng:
User behavior driven ranking without editorial judgments. CIKM 2010: 1473-1476 - [c5]Taesup Moon, Lihong Li, Wei Chu, Ciya Liao, Zhaohui Zheng, Yi Chang:
Online learning for recency search ranking using real-time user feedback. CIKM 2010: 1501-1504 - [c4]Taesup Moon, Alexander J. Smola, Yi Chang, Zhaohui Zheng:
IntervalRank: isotonic regression with listwise and pairwise constraints. WSDM 2010: 151-160 - [i3]Taesup Moon, Tsachy Weissman, Jae-Young Kim:
Discrete denoising of heterogenous two-dimensional data. CoRR abs/1007.1799 (2010)
2000 – 2009
- 2009
- [j3]Taesup Moon, Tsachy Weissman:
Discrete denoising with shifts. IEEE Trans. Inf. Theory 55(11): 5284-5301 (2009) - [j2]Taesup Moon, Tsachy Weissman:
Universal FIR MMSE Filtering. IEEE Trans. Signal Process. 57(3): 1068-1083 (2009) - 2008
- [j1]Taesup Moon, Tsachy Weissman:
Universal Filtering Via Hidden Markov Modeling. IEEE Trans. Inf. Theory 54(2): 692-708 (2008) - 2007
- [c3]Taesup Moon, Tsachy Weissman:
Competitive On-line Linear FIR MMSE Filtering. ISIT 2007: 1126-1130 - [i2]Taesup Moon, Tsachy Weissman:
Discrete Denoising with Shifts. CoRR abs/0708.2566 (2007) - 2006
- [c2]Yejin Kim, Hyeon Bae, Kyungmin Poo, Jongrack Kim, Taesup Moon, Sungshin Kim, Changwon Kim:
Soft Sensor Using PNN Model and Rule Base for Wastewater Treatment Plant. ISNN (2) 2006: 1261-1269 - [i1]Taesup Moon, Tsachy Weissman:
Universal Filtering via Hidden Markov Modeling. CoRR abs/cs/0605077 (2006) - 2005
- [c1]Taesup Moon, Tsachy Weissman:
Discrete universal filtering via hidden Markov modelling. ISIT 2005: 1285-1289
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from , , and to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-12-10 20:49 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint