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06/23/2023
Estimating Residential Solar Potential Using Aerial Data
Project Sunroof estimates the solar potential of residential buildings u...
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06/15/2023
Block-State Transformer
State space models (SSMs) have shown impressive results on tasks that re...
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04/25/2023
Proto-Value Networks: Scaling Representation Learning with Auxiliary Tasks
Auxiliary tasks improve the representations learned by deep reinforcemen...
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11/03/2021
Learned Image Compression for Machine Perception
Recent work has shown that learned image compression strategies can outp...
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08/07/2021
Impact of Aliasing on Generalization in Deep Convolutional Networks
We investigate the impact of aliasing on generalization in Deep Convolut...
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04/06/2021
Comparing Transfer and Meta Learning Approaches on a Unified Few-Shot Classification Benchmark
Meta and transfer learning are two successful families of approaches to ...
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01/08/2020
An Analysis of Object Representations in Deep Visual Trackers
Fully convolutional deep correlation networks are integral components of...
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03/07/2019
Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples
Few-shot classification refers to learning a classifier for new classes ...
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11/11/2016
Learning to Navigate in Complex Environments
Learning to navigate in complex environments with dynamic elements is an...
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06/09/2015
Learning to Linearize Under Uncertainty
Training deep feature hierarchies to solve supervised learning tasks has...
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06/08/2015
Stacked What-Where Auto-encoders
We present a novel architecture, the "stacked what-where auto-encoders" ...
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04/09/2015
Unsupervised Feature Learning from Temporal Data
Current state-of-the-art classification and detection algorithms rely on...
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12/18/2014
Unsupervised Learning of Spatiotemporally Coherent Metrics
Current state-of-the-art classification and detection algorithms rely on...
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11/16/2014