--- title: "Other — papers, page 30" description: "Other: 743 papers of the Elamur Research library · page 30 of 30 — our summary of each, its ideas, references and who cites it." canonical: "https://research.elamur.ai/free/en/shelves/other/page/30/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/shelves/other/page/30/) [home](https://md.research.elamur.ai/free/en/) / [shelves](https://md.research.elamur.ai/free/en/shelves/) / [Other](https://md.research.elamur.ai/free/en/shelves/other/) / page 30 # 📦 Other 743 papers · page 30 of 30 · newest first · [all shelves](https://md.research.elamur.ai/free/en/shelves/) Works whose topics fit none of the fields above yet. [← prev](https://md.research.elamur.ai/free/en/shelves/other/page/29/) [1](https://md.research.elamur.ai/free/en/shelves/other/) … [29](https://md.research.elamur.ai/free/en/shelves/other/page/29/) **30** - [Explaining and Harnessing Adversarial Examples](https://md.research.elamur.ai/free/en/papers/goodfellow-2014-explaining-harnessing-adversarial-examples/) — Ian J. Goodfellow, Jonathon Shlens, Christian Szegedy · 2014 - [ImageNet Large Scale Visual Recognition Challenge](https://md.research.elamur.ai/free/en/papers/russakovsky-2014-imagenet-large-scale-visual-recognition/) — Olga Russakovsky, Jia Deng, Hao Su, et al. · 2014 - [Long-term Recurrent Convolutional Networks for Visual Recognition and Description](https://md.research.elamur.ai/free/en/papers/donahue-2014-long-term-recurrent-convolutional-networks/) — Jeff Donahue, Lisa Anne Hendricks, Marcus Rohrbach, et al. · 2014 - [Microsoft COCO: Common Objects in Context](https://md.research.elamur.ai/free/en/papers/lin-2014-microsoft-coco-common-objects-context/) — Tsung-Yi Lin, Michael Maire, Serge Belongie, et al. · 2014 - [Recurrent Neural Network Regularization](https://md.research.elamur.ai/free/en/papers/zaremba-2014-recurrent-neural-network-regularization/) — Wojciech Zaremba, Ilya Sutskever, Oriol Vinyals · 2014 - [Show and Tell: A Neural Image Caption Generator](https://md.research.elamur.ai/free/en/papers/vinyals-2014-show-tell-neural-image-caption/) — Oriol Vinyals, Alexander Toshev, Samy Bengio, et al. · 2014 - [Stochastic Backpropagation and Approximate Inference in Deep Generative Models](https://md.research.elamur.ai/free/en/papers/rezende-2014-stochastic-backpropagation-approximate-inference-deep/) — Danilo Jimenez Rezende, Shakir Mohamed, Daan Wierstra · 2014 - [Unifying Visual-Semantic Embeddings with Multimodal Neural Language Models](https://md.research.elamur.ai/free/en/papers/kiros-2014-unifying-visual-semantic-embeddings-multimodal/) — Ryan Kiros, Ruslan Salakhutdinov, Richard S. Zemel · 2014 - [Very Deep Convolutional Networks for Large-Scale Image Recognition](https://md.research.elamur.ai/free/en/papers/simonyan-2014-very-deep-convolutional-networks-large/) — Karen Simonyan, Andrew Zisserman · 2014 - [Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps](https://md.research.elamur.ai/free/en/papers/simonyan-2013-deep-inside-convolutional-networks-visualising/) — Karen Simonyan, Andrea Vedaldi, Andrew Zisserman · 2013 - [One Billion Word Benchmark for Measuring Progress in Statistical Language Modeling](https://md.research.elamur.ai/free/en/papers/chelba-2013-one-billion-word-benchmark-measuring/) — Ciprian Chelba, Tomas Mikolov, Mike Schuster, et al. · 2013 - [Rich feature hierarchies for accurate object detection and semantic segmentation](https://md.research.elamur.ai/free/en/papers/girshick-2013-rich-feature-hierarchies-accurate-object/) — Ross Girshick, Jeff Donahue, Trevor Darrell, et al. · 2013 - [Visualizing and Understanding Convolutional Networks](https://md.research.elamur.ai/free/en/papers/zeiler-2013-visualizing-understanding-convolutional-networks/) — Matthew D Zeiler, Rob Fergus · 2013 - [ADADELTA: An Adaptive Learning Rate Method](https://md.research.elamur.ai/free/en/papers/zeiler-2012-adadelta-adaptive-learning-rate-method/) — Matthew D. Zeiler · 2012 - [Representation Learning: A Review and New Perspectives](https://md.research.elamur.ai/free/en/papers/bengio-2012-representation-learning-review-new-perspectives/) — Yoshua Bengio, Aaron Courville, Pascal Vincent · 2012 - [Sequence Transduction with Recurrent Neural Networks](https://md.research.elamur.ai/free/en/papers/graves-2012-sequence-transduction-recurrent-neural-networks/) — Alex Graves · 2012 - [A Tale of Two Parsers: Investigating and Combining Graph-based and Transition-based Dependency Parsing](https://md.research.elamur.ai/free/en/papers/zhang-2008-tale-two-parsers-investigating-combining/) — Yue Zhang, Stephen Clark · 2008 - [TnT – A Statistical Part-of-Speech Tagger](https://md.research.elamur.ai/free/en/papers/brants-2000-tnt-statistical-part-speech-tagger/) — Thorsten Brants · 2000 [← prev](https://md.research.elamur.ai/free/en/shelves/other/page/29/) [1](https://md.research.elamur.ai/free/en/shelves/other/) … [29](https://md.research.elamur.ai/free/en/shelves/other/page/29/) **30**