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08/16/2023
Painter: Teaching Auto-regressive Language Models to Draw Sketches
Large language models (LLMs) have made tremendous progress in natural la...
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06/30/2023
Look, Remember and Reason: Visual Reasoning with Grounded Rationales
Large language models have recently shown human level performance on a v...
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06/06/2023
Deductive Verification of Chain-of-Thought Reasoning
Large Language Models (LLMs) significantly benefit from Chain-of-Thought...
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05/14/2023
Is end-to-end learning enough for fitness activity recognition?
End-to-end learning has taken hold of many computer vision tasks, in par...
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11/11/2022
Metaphors We Learn By
Gradient based learning using error back-propagation (“backprop”) is a w...
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09/04/2018
Hierarchical Video Understanding
We introduce a hierarchical architecture for video understanding that ex...
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04/24/2018
Fine-grained Video Classification and Captioning
We describe a DNN for fine-grained action classification and video capti...
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06/13/2017
The "something something" video database for learning and evaluating visual common sense
Neural networks trained on datasets such as ImageNet have led to major a...
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05/09/2016
Theano: A Python framework for fast computation of mathematical expressions
Theano is a Python library that allows to define, optimize, and evaluate...
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02/26/2016
Architectural Complexity Measures of Recurrent Neural Networks
In this paper, we systematically analyze the connecting architectures of...
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02/16/2016
Generating images with recurrent adversarial networks
Gatys et al. (2015) showed that optimizing pixels to match features in a...
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11/26/2015
Regularizing RNNs by Stabilizing Activations
We stabilize the activations of Recurrent Neural Networks (RNNs) by pena...
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11/09/2015
How far can we go without convolution: Improving fully-connected networks
We propose ways to improve the performance of fully connected networks. ...
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10/11/2015
Neural Networks with Few Multiplications
For most deep learning algorithms training is notoriously time consuming...
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06/29/2015
Dropout as data augmentation
Dropout is typically interpreted as bagging a large number of models sha...
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03/05/2015
EmoNets: Multimodal deep learning approaches for emotion recognition in video
The task of the emotion recognition in the wild (EmotiW) Challenge is to...
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12/05/2014
On Using Very Large Target Vocabulary for Neural Machine Translation
Neural machine translation, a recently proposed approach to machine tran...
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02/13/2014
Zero-bias autoencoders and the benefits of co-adapting features
Regularized training of an autoencoder typically results in hidden unit ...
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02/10/2014
Modeling sequential data using higher-order relational features and predictive training
Bi-linear feature learning models, like the gated autoencoder, were prop...
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12/12/2013
Unsupervised learning of depth and motion
We present a model for the joint estimation of disparity and motion. The...
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06/13/2013
Learning to encode motion using spatio-temporal synchrony
We consider the task of learning to extract motion from videos. To this ...
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06/18/2012
On multi-view feature learning
Sparse coding is a common approach to learning local features for object...
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10/01/2011