Google
Google Scholar
Semantic Scholar
MS Academic
CiteSeerX
ORCIDJakob J. Verbeek
Jakob Verbeek
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2021
[i26]Nitika Verma, Adnane Boukhayma, Jakob Verbeek, Edmond Boyer:
DualConv: Dual Mesh Convolutional Networks for Shape Correspondence. CoRR abs/2103.12459 (2021)- 2020
- [c64]Maha Elbayad, Michael Ustaszewski, Emmanuelle Esperança-Rodier, Francis Brunet-Manquat, Jakob Verbeek, Laurent Besacier:
Online Versus Offline NMT Quality: An In-depth Analysis on English-German and German-English. COLING 2020: 5047-5058 - [c63]Xiaotian Li, Shuzhe Wang, Yi Zhao, Jakob Verbeek, Juho Kannala:
Hierarchical Scene Coordinate Classification and Regression for Visual Localization. CVPR 2020: 11980-11989 - [c62]Roman Klokov
, Edmond Boyer, Jakob Verbeek:
Discrete Point Flow Networks for Efficient Point Cloud Generation. ECCV (23) 2020: 694-710 - [c61]Ekaterina Iakovleva, Jakob Verbeek, Karteek Alahari:
Meta-Learning with Shared Amortized Variational Inference. ICML 2020: 4572-4582 - [c60]Maha Elbayad, Laurent Besacier, Jakob Verbeek:
Efficient Wait-k Models for Simultaneous Machine Translation. INTERSPEECH 2020: 1461-1465 - [i25]Adria Ruiz, Jakob Verbeek:
Distilled Hierarchical Neural Ensembles with Adaptive Inference Cost. CoRR abs/2003.01474 (2020) - [i24]Maha Elbayad, Laurent Besacier, Jakob Verbeek:
Efficient Wait-k Models for Simultaneous Machine Translation. CoRR abs/2005.08595 (2020) - [i23]Roman Klokov, Edmond Boyer, Jakob Verbeek:
Discrete Point Flow Networks for Efficient Point Cloud Generation. CoRR abs/2007.10170 (2020) - [i22]Ekaterina Iakovleva, Jakob Verbeek, Karteek Alahari:
Meta-Learning with Shared Amortized Variational Inference. CoRR abs/2008.12037 (2020)
2010 – 2019
- 2019
- [c59]Roman Klokov, Jakob Verbeek, Edmond Boyer:
Probabilistic Reconstruction Networks for 3D Shape Inference from a Single Image. BMVC 2019: 165 - [c58]Adria Ruiz, Jakob Verbeek:
Adaptative Inference Cost With Convolutional Neural Mixture Models. ICCV 2019: 1872-1881 - [c57]Mariia Vladimirova, Jakob Verbeek, Pablo Mesejo, Julyan Arbel:
Understanding Priors in Bayesian Neural Networks at the Unit Level. ICML 2019: 6458-6467 - [c56]Thomas Lucas, Konstantin Shmelkov, Karteek Alahari, Cordelia Schmid, Jakob Verbeek:
Adaptive Density Estimation for Generative Models. NeurIPS 2019: 11993-12003 - [i21]Konstantin Shmelkov, Thomas Lucas, Karteek Alahari, Cordelia Schmid, Jakob Verbeek:
Coverage and Quality Driven Training of Generative Image Models. CoRR abs/1901.01091 (2019) - [i20]Adria Ruiz, Oriol Martínez, Xavier Binefa, Jakob Verbeek:
Learning Disentangled Representations with Reference-Based Variational Autoencoders. CoRR abs/1901.08534 (2019) - [i19]Adria Ruiz, Jakob Verbeek:
Adaptative Inference Cost With Convolutional Neural Mixture Models. CoRR abs/1908.06694 (2019) - [i18]Roman Klokov, Jakob Verbeek, Edmond Boyer:
Probabilistic Reconstruction Networks for 3D Shape Inference from a Single Image. CoRR abs/1908.07475 (2019) - [i17]Xiaotian Li, Jakob Verbeek, Juho Kannala:
Hierarchical Joint Scene Coordinate Classification and Regression for Visual Localization. CoRR abs/1909.06216 (2019) - 2018
- [j21]Valentina Zadrija, Josip Krapac, Sinisa Segvic, Jakob Verbeek:
Sparse weakly supervised models for object localization in road environment. Comput. Vis. Image Underst. 176-177: 9-21 (2018) - [j20]Guosheng Hu, Xiaojiang Peng, Yongxin Yang, Timothy M. Hospedales, Jakob Verbeek:
Frankenstein: Learning Deep Face Representations Using Small Data. IEEE Trans. Image Process. 27(1): 293-303 (2018) - [c55]Maha Elbayad, Laurent Besacier, Jakob Verbeek:
Token-level and sequence-level loss smoothing for RNN language models. ACL (1) 2018: 2094-2103 - [c54]Maha Elbayad, Laurent Besacier, Jakob Verbeek:
Pervasive Attention: 2D Convolutional Neural Networks for Sequence-to-Sequence Prediction. CoNLL 2018: 97-107 - [c53]Nitika Verma, Edmond Boyer, Jakob Verbeek:
FeaStNet: Feature-Steered Graph Convolutions for 3D Shape Analysis. CVPR 2018: 2598-2606 - [c52]Camille Couprie, Pauline Luc, Jakob Verbeek:
Joint Future Semantic and Instance Segmentation Prediction. ECCV Workshops (3) 2018: 154-168 - [c51]Xiaotian Li, Juha Ylioinas, Jakob Verbeek, Juho Kannala:
Scene Coordinate Regression with Angle-Based Reprojection Loss for Camera Relocalization. ECCV Workshops (3) 2018: 229-245 - [c50]Pauline Luc, Camille Couprie, Yann LeCun, Jakob Verbeek:
Predicting Future Instance Segmentation by Forecasting Convolutional Features. ECCV (9) 2018: 593-608 - [c49]Thomas Lucas, Corentin Tallec, Yann Ollivier, Jakob Verbeek:
Mixed batches and symmetric discriminators for GAN training. ICML 2018: 2850-2859 - [c48]Thomas Lucas, Jakob Verbeek:
Auxiliary Guided Autoregressive Variational Autoencoders. ECML/PKDD (1) 2018: 443-458 - [i16]Pauline Luc, Camille Couprie, Yann LeCun, Jakob Verbeek:
Predicting Future Instance Segmentations by Forecasting Convolutional Features. CoRR abs/1803.11496 (2018) - [i15]Maha Elbayad, Laurent Besacier, Jakob Verbeek:
Token-level and sequence-level loss smoothing for RNN language models. CoRR abs/1805.05062 (2018) - [i14]Thomas Lucas, Corentin Tallec, Jakob Verbeek, Yann Ollivier:
Mixed batches and symmetric discriminators for GAN training. CoRR abs/1806.07185 (2018) - [i13]Maha Elbayad, Laurent Besacier, Jakob Verbeek:
Pervasive Attention: 2D Convolutional Neural Networks for Sequence-to-Sequence Prediction. CoRR abs/1808.03867 (2018) - [i12]Xiaotian Li, Juha Ylioinas, Jakob Verbeek, Juho Kannala:
Scene Coordinate Regression with Angle-Based Reprojection Loss for Camera Relocalization. CoRR abs/1808.04999 (2018) - 2017
- [j19]Ramazan Gokberk Cinbis, Jakob J. Verbeek, Cordelia Schmid:
Weakly Supervised Object Localization with Multi-Fold Multiple Instance Learning. IEEE Trans. Pattern Anal. Mach. Intell. 39(1): 189-203 (2017) - [c47]Pauline Luc, Natalia Neverova, Camille Couprie, Jakob Verbeek, Yann LeCun:
Predicting Deeper into the Future of Semantic Segmentation. ICCV 2017: 648-657 - [c46]Marco Pedersoli, Thomas Lucas, Cordelia Schmid, Jakob Verbeek:
Areas of Attention for Image Captioning. ICCV 2017: 1251-1259 - [i11]Natalia Neverova, Pauline Luc, Camille Couprie, Jakob J. Verbeek, Yann LeCun:
Predicting Deeper into the Future of Semantic Segmentation. CoRR abs/1703.07684 (2017) - [i10]Nitika Verma, Edmond Boyer, Jakob Verbeek:
Dynamic Filters in Graph Convolutional Networks. CoRR abs/1706.05206 (2017) - [i9]Thomas Lucas, Jakob Verbeek:
Auxiliary Guided Autoregressive Variational Autoencoders. CoRR abs/1711.11479 (2017) - 2016
- [b2]Jakob Verbeek:
Machine learning solutions to visual recognition problems. Grenoble Alpes University, France, 2016 - [j18]Heng Wang, Dan Oneata, Jakob J. Verbeek, Cordelia Schmid:
A Robust and Efficient Video Representation for Action Recognition. Int. J. Comput. Vis. 119(3): 219-238 (2016) - [j17]Matthijs Douze, Jérôme Revaud, Jakob J. Verbeek, Hervé Jégou, Cordelia Schmid:
Circulant Temporal Encoding for Video Retrieval and Temporal Alignment. Int. J. Comput. Vis. 119(3): 291-306 (2016) - [j16]Ramazan Gokberk Cinbis, Jakob J. Verbeek, Cordelia Schmid:
Approximate Fisher Kernels of Non-iid Image Models for Image Categorization. IEEE Trans. Pattern Anal. Mach. Intell. 38(6): 1084-1098 (2016) - [c45]Shreyas Saxena, Jakob Verbeek:
Heterogeneous Face Recognition with CNNs. ECCV Workshops (3) 2016: 483-491 - [c44]Shreyas Saxena, Jakob Verbeek:
Convolutional Neural Fabrics. NIPS 2016: 4053-4061 - [i8]Guosheng Hu, Xiaojiang Peng, Yongxin Yang, Timothy M. Hospedales, Jakob Verbeek:
Frankenstein: Learning Deep Face Representations using Small Data. CoRR abs/1603.06470 (2016) - [i7]Shreyas Saxena, Jakob Verbeek:
Convolutional Neural Fabrics. CoRR abs/1606.02492 (2016) - [i6]Pauline Luc, Camille Couprie, Soumith Chintala, Jakob Verbeek:
Semantic Segmentation using Adversarial Networks. CoRR abs/1611.08408 (2016) - [i5]Marco Pedersoli, Thomas Lucas, Cordelia Schmid, Jakob Verbeek:
Areas of Attention for Image Captioning. CoRR abs/1612.01033 (2016) - 2015
- [c43]Valentina Zadrija, Josip Krapac, Jakob J. Verbeek, Sinisa Segvic:
Patch-Level Spatial Layout for Classification and Weakly Supervised Localization. GCPR 2015: 492-503 - [c42]Shreyas Saxena, Jakob Verbeek:
Coordinated Local Metric Learning. ICCV Workshops 2015: 369-377 - [i4]Ramazan Gokberk Cinbis, Jakob J. Verbeek, Cordelia Schmid:
Weakly Supervised Object Localization with Multi-fold Multiple Instance Learning. CoRR abs/1503.00949 (2015) - [i3]Heng Wang, Dan Oneata, Jakob J. Verbeek, Cordelia Schmid:
A robust and efficient video representation for action recognition. CoRR abs/1504.05524 (2015) - [i2]Matthijs Douze, Jérôme Revaud, Jakob J. Verbeek, Hervé Jégou, Cordelia Schmid:
Circulant temporal encoding for video retrieval and temporal alignment. CoRR abs/1506.02588 (2015) - [i1]Ramazan Gokberk Cinbis, Jakob J. Verbeek, Cordelia Schmid:
Approximate Fisher Kernels of non-iid Image Models for Image Categorization. CoRR abs/1510.00857 (2015) - 2014
- [c41]Ramazan Gokberk Cinbis, Jakob J. Verbeek, Cordelia Schmid:
Multi-fold MIL Training for Weakly Supervised Object Localization. CVPR 2014: 2409-2416 - [c40]Dan Oneata, Jakob J. Verbeek, Cordelia Schmid:
Efficient Action Localization with Approximately Normalized Fisher Vectors. CVPR 2014: 2545-2552 - [c39]Dan Oneata, Jérôme Revaud, Jakob J. Verbeek, Cordelia Schmid:
Spatio-temporal Object Detection Proposals. ECCV (3) 2014: 737-752 - [c38]Matthijs Douze, Dan Oneata, Mattis Paulin, Clément Leray, Nicolas Chesneau, Danila Potapov, Jakob Verbeek, Karteek Alahari, Zaïd Harchaoui, Lori Lamel, Jean-Luc Gauvain, Christoph Schmidt, Cordelia Schmid:
The INRIA-LIM-VocR and AXES submissions to TrecVid 2014 Multimedia Event Detection. TRECVID 2014 - 2013
- [j15]Jorge Sánchez, Florent Perronnin, Thomas Mensink, Jakob J. Verbeek:
Image Classification with the Fisher Vector: Theory and Practice. Int. J. Comput. Vis. 105(3): 222-245 (2013) - [j14]Thomas Mensink, Jakob J. Verbeek, Gabriela Csurka:
Tree-Structured CRF Models for Interactive Image Labeling. IEEE Trans. Pattern Anal. Mach. Intell. 35(2): 476-489 (2013) - [j13]Thomas Mensink, Jakob J. Verbeek, Florent Perronnin, Gabriela Csurka:
Distance-Based Image Classification: Generalizing to New Classes at Near-Zero Cost. IEEE Trans. Pattern Anal. Mach. Intell. 35(11): 2624-2637 (2013) - [c37]Dan Oneata, Jakob J. Verbeek, Cordelia Schmid:
Action and Event Recognition with Fisher Vectors on a Compact Feature Set. ICCV 2013: 1817-1824 - [c36]Ramazan Gokberk Cinbis, Jakob J. Verbeek, Cordelia Schmid:
Segmentation Driven Object Detection with Fisher Vectors. ICCV 2013: 2968-2975 - [c35]Hervé Bredin, Johann Poignant, Guillaume Fortier, Makarand Tapaswi, Viet Bac Le, Anindya Roy, Claude Barras, Sophie Rosset, Achintya Kumar Sarkar, Qian Yang, Hua Gao, Alexis Mignon, Jakob J. Verbeek, Laurent Besacier, Georges Quénot, Hazim Kemal Ekenel, Rainer Stiefelhagen:
QCompere @ REPERE 2013. SLAM@INTERSPEECH 2013: 49-54 - [c34]Robin Aly, Relja Arandjelovic, Ken Chatfield, Matthijs Douze, Basura Fernando, Zaïd Harchaoui, Kevin McGuinness, Noel E. O'Connor, Dan Oneata, Omkar M. Parkhi, Danila Potapov, Jérôme Revaud, Cordelia Schmid, Jochen Schwenninger, David Scott, Tinne Tuytelaars, Jakob Verbeek, Heng Wang, Andrew Zisserman:
The AXES submissions at TRECVID 2013. TRECVID 2013 - [p1]Thomas Mensink, Jakob Verbeek, Florent Perronnin:
Large Scale Metric Learning for Distance-Based Image Classification on Open Ended Data Sets. Advanced Topics in Computer Vision 2013: 243-276 - 2012
- [j12]Matthieu Guillaumin, Thomas Mensink, Jakob J. Verbeek, Cordelia Schmid:
Face Recognition from Caption-Based Supervision. Int. J. Comput. Vis. 96(1): 64-82 (2012) - [c33]Ramazan Gokberk Cinbis, Jakob J. Verbeek, Cordelia Schmid:
Image categorization using Fisher kernels of non-iid image models. CVPR 2012: 2184-2191 - [c32]Hervé Bredin, Johann Poignant, Makarand Tapaswi, Guillaume Fortier, Viet Bac Le, Thibault Napoléon, Hua Gao, Claude Barras, Sophie Rosset, Laurent Besacier, Jakob J. Verbeek, Georges Quénot, Frédéric Jurie, Hazim Kemal Ekenel:
Fusion of Speech, Faces and Text for Person Identification in TV Broadcast. ECCV Workshops (3) 2012: 385-394 - [c31]Thomas Mensink, Jakob J. Verbeek, Florent Perronnin, Gabriela Csurka:
Metric Learning for Large Scale Image Classification: Generalizing to New Classes at Near-Zero Cost. ECCV (2) 2012: 488-501 - [c30]Robin Aly, Kevin McGuinness, Shu Chen, Noel E. O'Connor, Ken Chatfield, Omkar M. Parkhi, Relja Arandjelovic, Andrew Zisserman, Basura Fernando, Tinne Tuytelaars, Dan Oneata, Matthijs Douze, Jérôme Revaud, Jochen Schwenninger, Danila Potapov, Heng Wang, Zaïd Harchaoui, Jakob Verbeek, Cordelia Schmid:
AXES at TRECVID 2012: KIS, INS, and MED. TRECVID 2012 - 2011
- [c29]Josip Krapac, Jakob J. Verbeek, Frédéric Jurie:
Learning Tree-structured Quantizers for Image Categorization. BMVC 2011: 1-11 - [c28]Thomas Mensink, Jakob J. Verbeek, Gabriela Csurka:
Learning structured prediction models for interactive image labeling. CVPR 2011: 833-840 - [c27]Josip Krapac, Jakob J. Verbeek, Frédéric Jurie:
Modeling spatial layout with fisher vectors for image categorization. ICCV 2011: 1487-1494 - [c26]Ramazan Gokberk Cinbis, Jakob J. Verbeek, Cordelia Schmid:
Unsupervised metric learning for face identification in TV video. ICCV 2011: 1559-1566 - 2010
- [j11]Diane Larlus, Jakob J. Verbeek, Frédéric Jurie:
Category Level Object Segmentation by Combining Bag-of-Words Models with Dirichlet Processes and Random Fields. Int. J. Comput. Vis. 88(2): 238-253 (2010) - [j10]Hervé Jégou, Cordelia Schmid, Hedi Harzallah, Jakob J. Verbeek:
Accurate Image Search Using the Contextual Dissimilarity Measure. IEEE Trans. Pattern Anal. Mach. Intell. 32(1): 2-11 (2010) - [c25]Thomas Mensink, Jakob J. Verbeek, Gabriela Csurka:
Trans Media Relevance Feedback for Image Autoannotation. BMVC 2010: 1-12 - [c24]Thomas Mensink, Gabriela Csurka, Florent Perronnin, Jorge Sánchez, Jakob J. Verbeek:
LEAR and XRCE's Participation to Visual Concept Detection Task - ImageCLEF 2010. CLEF (Notebook Papers/LABs/Workshops) 2010 - [c23]Matthieu Guillaumin, Jakob J. Verbeek, Cordelia Schmid:
Multimodal semi-supervised learning for image classification. CVPR 2010: 902-909 - [c22]Josip Krapac, Moray Allan, Jakob J. Verbeek, Frédéric Jurie:
Improving web image search results using query-relative classifiers. CVPR 2010: 1094-1101 - [c21]Thomas Mensink, Jakob J. Verbeek, Bert Kappen:
EP for Efficient Stochastic Control with Obstacles. ECAI 2010: 675-680 - [c20]Matthieu Guillaumin, Jakob J. Verbeek, Cordelia Schmid:
Multiple Instance Metric Learning from Automatically Labeled Bags of Faces. ECCV (1) 2010: 634-647 - [c19]Jakob J. Verbeek, Matthieu Guillaumin, Thomas Mensink, Cordelia Schmid:
Image annotation with tagprop on the MIRFLICKR set. Multimedia Information Retrieval 2010: 537-546
2000 – 2009
- 2009
- [j9]Joost van de Weijer, Cordelia Schmid, Jakob J. Verbeek, Diane Larlus:
Learning Color Names for Real-World Applications. IEEE Trans. Image Process. 18(7): 1512-1523 (2009) - [c18]Moray Allan, Jakob J. Verbeek:
Ranking User-annotated Images for Multiple Query Terms. BMVC 2009: 1-10 - [c17]Matthijs Douze, Matthieu Guillaumin, Thomas Mensink, Cordelia Schmid, Jakob J. Verbeek:
INRIA-LEAR's Participation in ImageCLEF 2009. CLEF (Working Notes) 2009 - [c16]Matthieu Guillaumin, Thomas Mensink, Jakob J. Verbeek, Cordelia Schmid:
TagProp: Discriminative metric learning in nearest neighbor models for image auto-annotation. ICCV 2009: 309-316 - [c15]Matthieu Guillaumin, Jakob J. Verbeek, Cordelia Schmid:
Is that you? Metric learning approaches for face identification. ICCV 2009: 498-505 - 2008
- [c14]Matthieu Guillaumin, Thomas Mensink, Jakob J. Verbeek, Cordelia Schmid:
Automatic face naming with caption-based supervision. CVPR 2008 - [c13]Thomas Mensink, Jakob J. Verbeek:
Improving People Search Using Query Expansions. ECCV (2) 2008: 86-99 - [c12]Hakan Cevikalp, Jakob J. Verbeek, Frédéric Jurie, Alexander Kläser:
Semi-Supervised Dimensionality Reduction Using Pairwise Equivalence Constraints. VISAPP (1) 2008: 489-496 - 2007
- [c11]Jakob J. Verbeek, Bill Triggs:
Region Classification with Markov Field Aspect Models. CVPR 2007 - [c10]Joost van de Weijer, Cordelia Schmid, Jakob J. Verbeek:
Learning Color Names from Real-World Images. CVPR 2007 - [c9]Joost van de Weijer, Cordelia Schmid, Jakob J. Verbeek:
Using High-Level Visual Information for Color Constancy. ICCV 2007: 1-8 - [c8]Jakob J. Verbeek, Bill Triggs:
Scene Segmentation with CRFs Learned from Partially Labeled Images. NIPS 2007: 1553-1560 - 2006
- [j8]Jakob J. Verbeek, Jan Nunnink, Nikos A. Vlassis:
Accelerated EM-based clustering of large data sets. Data Min. Knowl. Discov. 13(3): 291-307 (2006) - [j7]Jakob J. Verbeek:
Learning Nonlinear Image Manifolds by Global Alignment of Local Linear Models. IEEE Trans. Pattern Anal. Mach. Intell. 28(8): 1236-1250 (2006) - [j6]Jakob J. Verbeek, Nikos A. Vlassis:
Gaussian fields for semi-supervised regression and correspondence learning. Pattern Recognit. 39(10): 1864-1875 (2006) - [c7]Zoran Zivkovic, Jakob J. Verbeek:
Transformation invariant component analysis for binary images. CVPR (1) 2006: 254-259 - 2005
- [j5]Josep M. Porta, Jakob J. Verbeek, Ben J. A. Kröse:
Active Appearance-Based Robot Localization Using Stereo Vision. Auton. Robots 18(1): 59-80 (2005) - [j4]Jakob J. Verbeek, Nikos A. Vlassis, Ben J. A. Kröse:
Self-organizing mixture models. Neurocomputing 63: 99-123 (2005) - 2004
- [b1]Jakob J. Verbeek:
Mixture models for clustering and dimension reduction. University of Amsterdam, Netherlands, 2004 - 2003
- [j3]Jakob J. Verbeek, Nikos A. Vlassis, Ben J. A. Kröse:
Efficient Greedy Learning of Gaussian Mixture Models. Neural Comput. 15(2): 469-485 (2003) - [j2]Aristidis Likas, Nikos A. Vlassis, Jakob J. Verbeek:
The global k-means clustering algorithm. Pattern Recognit. 36(2): 451-461 (2003) - [c6]Jakob J. Verbeek, Nikos A. Vlassis, Ben J. A. Kröse:
Self-Organization by Optimizing Free-Energy. ESANN 2003: 125-130 - [c5]Josep M. Porta, Jakob J. Verbeek, Ben J. A. Kröse:
Enhancing appearance-based robot localization using sparse disparity maps. IROS 2003: 980-985 - [c4]Jakob J. Verbeek, Sam T. Roweis, Nikos A. Vlassis:
Non-linear CCA and PCA by Alignment of Local Models. NIPS 2003: 297-304 - 2002
- [j1]Jakob J. Verbeek, Nikos A. Vlassis, Ben J. A. Kröse:
A k-segments algorithm for finding principal curves. Pattern Recognit. Lett. 23(8): 1009-1017 (2002) - [c3]Jakob J. Verbeek, Nikos A. Vlassis, Ben J. A. Kröse:
Fast nonlinear dimensionality reduction with topology representing networks. ESANN 2002: 193-198 - [c2]Jakob J. Verbeek, Nikos A. Vlassis, Ben J. A. Kröse:
Coordinating Principal Component Analyzers. ICANN 2002: 914-919 - 2001
- [c1]Jakob J. Verbeek, Nikos A. Vlassis, Ben J. A. Kröse:
A Soft k-Segments Algorithm for Principal Curves. ICANN 2001: 450-456
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).
load content from web.archive.org
Privacy notice: By enabling the option above, your browser will contact the API of web.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.
Tweets on dblp homepage
Show tweets from 
on the dblp homepage.
Privacy notice: By enabling the option above, your browser will contact twitter.com and twimg.com to load tweets curated by our Twitter account. At the same time, Twitter will persistently store several cookies with your web browser. While we did signal Twitter to not track our users by setting the "dnt" flag, we do not have any control over how Twitter uses your data. So please proceed with care and consider checking the Twitter privacy policy.
last updated on 2021-04-08 11:48 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
the dblp computer science bibliography is funded by:
