Search Results - "Espeholt, Lasse"

Deep learning for twelve hour precipitation forecasts by Espeholt, Lasse, Agrawal, Shreya, Sønderby, Casper, Kumar, Manoj, Heek, Jonathan, Bromberg, Carla, Gazen, Cenk, Carver, Rob, Andrychowicz, Marcin, Hickey, Jason, Bell, Aaron, Kalchbrenner, Nal

“…Existing weather forecasting models are based on physics and use supercomputers to evolve the atmosphere into the future. Better physics-based forecasts…”
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Deep Learning for Day Forecasts from Sparse Observations by Andrychowicz, Marcin, Espeholt, Lasse, Li, Di, Merchant, Samier, Merose, Alexander, Zyda, Fred, Agrawal, Shreya, Kalchbrenner, Nal

“…Deep neural networks offer an alternative paradigm for modeling weather conditions. The ability of neural models to make a prediction in less than a second…”
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Agent-Centric Representations for Multi-Agent Reinforcement Learning by Shang, Wenling, Espeholt, Lasse, Raichuk, Anton, Salimans, Tim

“…Object-centric representations have recently enabled significant progress in tackling relational reasoning tasks. By building a strong object-centric inductive…”
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SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference by Espeholt, Lasse, Marinier, Raphaël, Stanczyk, Piotr, Wang, Ke, Michalski, Marcin

“…We present a modern scalable reinforcement learning agent called SEED (Scalable, Efficient Deep-RL). By effectively utilizing modern accelerators, we show that…”
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Skillful Twelve Hour Precipitation Forecasts using Large Context Neural Networks by Espeholt, Lasse, Agrawal, Shreya, Sønderby, Casper, Kumar, Manoj, Heek, Jonathan, Bromberg, Carla, Gazen, Cenk, Hickey, Jason, Bell, Aaron, Kalchbrenner, Nal

“…The problem of forecasting weather has been scientifically studied for centuries due to its high impact on human lives, transportation, food production and…”
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Boosting Search Engines with Interactive Agents by Adolphs, Leonard, Boerschinger, Benjamin, Buck, Christian, Huebscher, Michelle Chen, Ciaramita, Massimiliano, Espeholt, Lasse, Hofmann, Thomas, Kilcher, Yannic, Rothe, Sascha, Sessa, Pier Giuseppe, Saralegui, Lierni Sestorain

“…This paper presents first successful steps in designing search agents that learn meta-strategies for iterative query refinement in information-seeking tasks…”
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MetNet: A Neural Weather Model for Precipitation Forecasting by Sønderby, Casper Kaae, Espeholt, Lasse, Heek, Jonathan, Dehghani, Mostafa, Oliver, Avital, Salimans, Tim, Agrawal, Shreya, Hickey, Jason, Kalchbrenner, Nal

“…Weather forecasting is a long standing scientific challenge with direct social and economic impact. The task is suitable for deep neural networks due to vast…”
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Multi-task Deep Reinforcement Learning with PopArt by Hessel, Matteo, Soyer, Hubert, Espeholt, Lasse, Czarnecki, Wojciech, Schmitt, Simon, van Hasselt, Hado

“…The reinforcement learning community has made great strides in designing algorithms capable of exceeding human performance on specific tasks. These algorithms…”
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Google Research Football: A Novel Reinforcement Learning Environment by Kurach, Karol, Raichuk, Anton, Stańczyk, Piotr, Zając, Michał, Bachem, Olivier, Espeholt, Lasse, Riquelme, Carlos, Vincent, Damien, Michalski, Marcin, Bousquet, Olivier, Gelly, Sylvain

“…Recent progress in the field of reinforcement learning has been accelerated by virtual learning environments such as video games, where novel algorithms and…”
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Neural Machine Translation in Linear Time by Kalchbrenner, Nal, Espeholt, Lasse, Simonyan, Karen, Oord, Aaron van den, Graves, Alex, Kavukcuoglu, Koray

“…We present a novel neural network for processing sequences. The ByteNet is a one-dimensional convolutional neural network that is composed of two parts, one to…”
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Conditional Image Generation with PixelCNN Decoders by Oord, Aaron van den, Kalchbrenner, Nal, Vinyals, Oriol, Espeholt, Lasse, Graves, Alex, Kavukcuoglu, Koray

“…This work explores conditional image generation with a new image density model based on the PixelCNN architecture. The model can be conditioned on any vector,…”
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IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures by Espeholt, Lasse, Soyer, Hubert, Munos, Remi, Simonyan, Karen, Mnih, Volodymir, Ward, Tom, Doron, Yotam, Firoiu, Vlad, Harley, Tim, Dunning, Iain, Legg, Shane, Kavukcuoglu, Koray

“…In this work we aim to solve a large collection of tasks using a single reinforcement learning agent with a single set of parameters. A key challenge is to…”
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Teaching Machines to Read and Comprehend by Hermann, Karl Moritz, Kočiský, Tomáš, Grefenstette, Edward, Espeholt, Lasse, Kay, Will, Suleyman, Mustafa, Blunsom, Phil

“…Teaching machines to read natural language documents remains an elusive challenge. Machine reading systems can be tested on their ability to answer questions…”
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