Karel Lenc

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All published works

Action	Title	Year	Authors
+ PDF Chat	Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context	2024	Gemini Team Machel Reid Nikolay Savinov Denis Teplyashin Dmitry Lepikhin Timothy Lillicrap Jean-baptiste Alayrac Radu Soricut Angeliki Lazaridou
+	Gemini: A Family of Highly Capable Multimodal Models	2023	Gemini Team Rohan Anil Sebastian Borgeaud Jean-Baptiste Alayrac Jiahui Yu Radu Soricut Johan Schalkwyk Andrew M. Dai Anja Hauth Katie Millican
+	Flamingo: a Visual Language Model for Few-Shot Learning	2022	Jean-Baptiste Alayrac Jeff Donahue Pauline Luc Antoine Miech Iain Barr Yana Hasson Karel Lenc Arthur Mensch Katie Millican Malcolm Reynolds
+ PDF Chat	Skilful precipitation nowcasting using deep generative models of radar	2021	Suman Ravuri Karel Lenc Matthew Willson Dmitry Kangin Rémi Lam Piotr Mirowski M. A. Fitzsimons Maria Athanassiadou Sheleem Kashem Sam Madge
+	Skillful Precipitation Nowcasting using Deep Generative Models of Radar	2021	Suman Ravuri Karel Lenc Matthew Willson Dmitry Kangin Rémi Lam Piotr Mirowski M. A. Fitzsimons Maria Athanassiadou Sheleem Kashem Sam Madge
+	Non-Differentiable Supervised Learning with Evolution Strategies and Hybrid Methods	2019	Karel Lenc Erich Elsen Tom Schaul Karen Simonyan
+ PDF Chat	HPatches: A benchmark and evaluation of handcrafted and learned local descriptors	2019	Vassileios Balntas Karel Lenc Andrea Vedaldi Tinne Tuytelaars Jiřı́ Matas Krystian Mikolajczyk
+	Large scale evaluation of local image feature detectors on homography datasets	2018	Karel Lenc Andrea Vedaldi
+ PDF Chat	Understanding Image Representations by Measuring Their Equivariance and Equivalence	2018	Karel Lenc Andrea Vedaldi
+	Large scale evaluation of local image feature detectors on homography datasets	2018	Karel Lenc Andrea Vedaldi
+ PDF Chat	HPatches: A Benchmark and Evaluation of Handcrafted and Learned Local Descriptors	2017	Vassileios Balntas Karel Lenc Andrea Vedaldi Krystian Mikolajczyk
+	HPatches: A benchmark and evaluation of handcrafted and learned local descriptors	2017	Vassileios Balntas Karel Lenc Andrea Vedaldi Krystian Mikolajczyk
+	HPatches: A benchmark and evaluation of handcrafted and learned local descriptors	2017	Vassileios Balntas Karel Lenc Andrea Vedaldi Krystian Mikolajczyk
+	Learning Covariant Feature Detectors	2016	Karel Lenc Andrea Vedaldi
+ PDF Chat	Learning Covariant Feature Detectors	2016	Karel Lenc Andrea Vedaldi
+	Learning Covariant Feature Detectors	2016	Karel Lenc Andrea Vedaldi
+	R-CNN minus R	2015	Karel Lenc Andrea Vedaldi
+ PDF Chat	Understanding image representations by measuring their equivariance and equivalence	2015	Karel Lenc Andrea Vedaldi
+	WxBS: Wide Baseline Stereo Generalizations	2015	Dmytro Mishkin Jiřı́ Matas Michal Perďoch Karel Lenc
+	WxBS: Wide Baseline Stereo Generalizations	2015	Dmytro Mishkin Jiřı́ Matas Michal Perďoch Karel Lenc
+	R-CNN minus R	2015	Karel Lenc Andrea Vedaldi
+	Understanding image representations by measuring their equivariance and equivalence	2014	Karel Lenc Andrea Vedaldi
+	MatConvNet - Convolutional Neural Networks for MATLAB	2014	Andrea Vedaldi Karel Lenc
+	Understanding image representations by measuring their equivariance and equivalence	2014	Karel Lenc Andrea Vedaldi

Common Coauthors

Coauthor	Papers Together
Andrea Vedaldi	16
Andrew Brock	5
Vassileios Balntas	4
Karen Simonyan	4
Krystian Mikolajczyk	4
Amol Mandhane	4
Sebastian Borgeaud	3
Oriol Vinyals	3
Katie Millican	3
Sina Samangooei	3
Roman Ring	3
Antoine Miech	3
Eliza Rutherford	3
Malcolm Reynolds	3
Jiřı́ Matas	3
Iain Barr	3
Sanjay Ghemawat	2
Balaji Lakshminarayanan	2
Jeremy Wiesner	2
Anudhyan Boral	2
Richard Tanburn	2
Vittorio Selo	2
Marianne Monteiro	2
Komal Jalan	2
Matthew Willson	2
Disha Shrivastava	2
Shuo-Yiin Chang	2
Jean-Baptiste Alayrac	2
Nithya Attaluri	2
Axel Stjerngren	2
Maxim Krikun	2
Alex Tomala	2
Arthur Guez	2
Ethan Dyer	2
Jack W. Rae	2
Mantas Pajarskas	2
James Molloy	2
Mukund Sundararajan	2
Yonghui Wu	2
David F. Steiner	2
Paul Komarek	2
Remi Crocker	2
Tianqi Liu	2
Olivier Dousse	2
Devendra Singh Sachan	2
Vincent J. Hellendoorn	2
Nina Martin	2
Ricardo Aguilar	2
Laura Knight	2
Ken Franko	2

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+ PDF Chat	Faster and Better: A Machine Learning Approach to Corner Detection	2008	Edward Rosten Reid Porter Tom Drummond	4
+ PDF Chat	ImageNet Large Scale Visual Recognition Challenge	2015	Olga Russakovsky Jia Deng Hao Su Jonathan Krause Sanjeev Satheesh Sean Ma Zhiheng Huang Andrej Karpathy Aditya Khosla Michael S. Bernstein	4
+ PDF Chat	Learning to compare image patches via convolutional neural networks	2015	Sergey Zagoruyko Nikos Komodakis	4
+	Descriptor Matching with Convolutional Neural Networks: a Comparison to SIFT	2014	Philipp Fischer Alexey Dosovitskiy Thomas Brox	3
+	MatConvNet - Convolutional Neural Networks for MATLAB	2014	Andrea Vedaldi Karel Lenc	3
+	Learning Invariant Representations with Local Transformations	2012	Kihyuk Sohn Honglak Lee	3
+	Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps	2013	Karen Simonyan Andrea Vedaldi Andrew Zisserman	3
+ PDF Chat	LATCH: Learned arrangements of three patch codes	2016	Gil Levi Tal Hassner	3
+ PDF Chat	Learning to Assign Orientations to Feature Points	2016	Kwang Moo Yi Yannick Verdié Pascal Fua Vincent Lepetit	3
+	Return of the Devil in the Details: Delving Deep into Convolutional Nets	2014	Ken Chatfield Karen Simonyan Andrea Vedaldi Andrew Zisserman	3
+ PDF Chat	Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation	2014	Ross Girshick Jeff Donahue Trevor Darrell Jitendra Malik	2
+	Precipitation Nowcasting with Star-Bridge Networks	2019	Yuan Cao Qiuying Li Hongming Shan Zhizhong Huang Lei Chen Leiming Ma Junping Zhang	2
+	Very Deep Convolutional Networks for Large-Scale Image Recognition	2014	Karen Simonyan Andrew Zisserman	2
+	Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition	2014	Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun	2
+ PDF Chat	SuperPoint: Self-Supervised Interest Point Detection and Description	2018	Daniel DeTone Tomasz Malisiewicz Andrew Rabinovich	2
+	Visualizing and Understanding Convolutional Networks	2013	Matthew D. Zeiler Rob Fergus	2
+ PDF Chat	Computing the stereo matching cost with a convolutional neural network	2015	Jure Žbontar Yann LeCun	2
+	A review of radar-based nowcasting of precipitation and applicable machine learning techniques	2020	Rachel Prudden Samantha V. Adams Dmitry Kangin N. Robinson Suman Ravuri Shakir Mohamed Alberto Arribas	2
+	Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting	2015	Xingjian Shi Zhourong Chen Hao Wang Dit‐Yan Yeung Wai Kin Wong Wang‐chun Woo	2
+	Axial Attention in Multidimensional Transformers	2019	Jonathan Ho Nal Kalchbrenner Dirk Weissenborn Tim Salimans	2
+ PDF Chat	A machine learning nowcasting method based on real‐time reanalysis data	2017	Lei Han Juanzhen Sun Wei Zhang Yuanyuan Xiu Hailei Feng Y. Lin	2
+	DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition	2013	Jeff Donahue Yangqing Jia Oriol Vinyals Judy Hoffman Ning Zhang Eric Tzeng Trevor Darrell	2
+ PDF Chat	Stochastic Super-Resolution for Downscaling Time-Evolving Atmospheric Fields With a Generative Adversarial Network	2020	Jussi Leinonen Daniele Nerini Alexis Berne	2
+ PDF Chat	Detect What You Can: Detecting and Representing Objects Using Holistic Models and Body Parts	2014	Xianjie Chen Roozbeh Mottaghi Xiaobai Liu Sanja Fidler Raquel Urtasun Alan Yuille	2
+	MetNet: A Neural Weather Model for Precipitation Forecasting	2020	Casper Kaae Sønderby Lasse Espeholt Jonathan Heek Mostafa Dehghani Avital Oliver Tim Salimans Shreya Agrawal Jason Hickey Nal Kalchbrenner	2
+	Machine Learning for Precipitation Nowcasting from Radar Images	2019	Carla Bromberg Cenk Gazen Jason Hickey John Burge Luke Barrington Shreya Agrawal	2
+	DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition	2013	Jeff Donahue Yangqing Jia Oriol Vinyals Judy Hoffman Ning Zhang Eric Tzeng Trevor Darrell	2
+ PDF Chat	Image-to-Image Translation with Conditional Adversarial Networks	2017	Phillip Isola Jun-Yan Zhu Tinghui Zhou Alexei A. Efros	2
+	Learning to Compare Image Patches via Convolutional Neural Networks	2015	Sergey Zagoruyko Nikos Komodakis	2
+ PDF Chat	CNN Features Off-the-Shelf: An Astounding Baseline for Recognition	2014	Ali Sharif Razavian Hossein Azizpour Josephine Sullivan Stefan Carlsson	2
+ PDF Chat	Multi-scale Orderless Pooling of Deep Convolutional Activation Features	2014	Yunchao Gong Liwei Wang Ruiqi Guo Svetlana Lazebnik	2
+	Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift	2015	Sergey Ioffe Christian Szegedy	2
+	Predicting Parameters in Deep Learning	2013	Misha Denil Babak Shakibi Laurent Dinh Marc’Aurelio Ranzato Nando de Freitas	2
+ PDF Chat	Visualizing Deep Convolutional Neural Networks Using Natural Pre-images	2016	Aravindh Mahendran Andrea Vedaldi	1
+	Convergent Learning: Do different neural networks learn the same representations?	2015	Yixuan Li Jason Yosinski Jeff Clune Hod Lipson John E. Hopcroft	1
+ PDF Chat	Rotation-invariant convolutional neural networks for galaxy morphology prediction	2015	Sander Dieleman Kyle Willett Joni Dambre	1
+ PDF Chat	Domain-size pooling in local descriptors: DSP-SIFT	2015	Jingming Dong Stefano Soatto	1
+ PDF Chat	Natural Evolution Strategies	2008	Daan Wierstra Tom Schaul Jan Peters Juergen Schmidhuber	1
+	Discriminative Unsupervised Feature Learning with Convolutional Neural Networks	2014	Alexey Dosovitskiy Jost Tobias Springenberg Martin Riedmiller Thomas Brox	1
+	Return of the Devil in the Details: Delving Deep into Convolutional Nets	2014	Ken Chatfield Karen Simonyan Andrea Vedaldi Andrew Zisserman	1
+	Faster gaze prediction with dense networks and Fisher pruning	2018	Lucas Theis Iryna Korshunova Alykhan Tejani Ferenc Huszár	1
+	On the Relationship Between the OpenAI Evolution Strategy and Stochastic Gradient Descent	2017	Xingwen Zhang Jeff Clune Kenneth O. Stanley	1
+	Deep Rewiring: Training very sparse deep networks	2017	Guillaume Bellec David Kappel Wolfgang Maass Robert Legenstein	1
+ PDF Chat	What Makes for Effective Detection Proposals?	2015	Jan Hosang Rodrigo Benenson Piotr Dollár Bernt Schiele	1
+	Very Deep Convolutional Networks for Large-Scale Image Recognition	2014	Karen Simonyan Andrew Zisserman	1
+	Don't Decay the Learning Rate, Increase the Batch Size	2017	Samuel Smith Pieter-Jan Kindermans Chris Ying Quoc V. Le	1
+	To prune, or not to prune: exploring the efficacy of pruning for model compression	2017	Michael Zhu Suyog Gupta	1
+	On Calibration of Modern Neural Networks	2017	Chuan Guo Geoff Pleiss Yu Sun Kilian Q. Weinberger	1
+	Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model	2017	Xingjian Shi Zhihan Gao Leonard Lausen Hao Wang Dit‐Yan Yeung Wai Kin Wong Wang‐chun Woo	1
+	Conditional Generative Adversarial Nets	2014	Mehdi Mirza Simon Osindero	1