Search Results - "Merzic, Hamza"

Leveraging Contact Forces for Learning to Grasp by Merzic, Hamza, Bogdanovic, Miroslav, Kappler, Daniel, Righetti, Ludovic, Bohg, Jeannette

“…Grasping objects under uncertainty remains an open problem in robotics research. This uncertainty is often due to noisy or partial observations of the object…”
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Data curation via joint example selection further accelerates multimodal learning by Evans, Talfan, Parthasarathy, Nikhil, Merzic, Hamza, Henaff, Olivier J

“…Data curation is an essential component of large-scale pretraining. In this work, we demonstrate that jointly selecting batches of data is more effective for…”
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Bad Students Make Great Teachers: Active Learning Accelerates Large-Scale Visual Understanding by Evans, Talfan, Pathak, Shreya, Merzic, Hamza, Schwarz, Jonathan, Tanno, Ryutaro, Henaff, Olivier J

“…Power-law scaling indicates that large-scale training with uniform sampling is prohibitively slow. Active learning methods aim to increase data efficiency by…”
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Grounded Language Learning Fast and Slow by Hill, Felix, Tieleman, Olivier, von Glehn, Tamara, Wong, Nathaniel, Merzic, Hamza, Clark, Stephen

“…Recent work has shown that large text-based neural language models, trained with conventional supervised learning objectives, acquire a surprising propensity…”
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Leveraging Contact Forces for Learning to Grasp by Merzic, Hamza, Bogdanovic, Miroslav, Kappler, Daniel, Righetti, Ludovic, Bohg, Jeannette

“…Grasping objects under uncertainty remains an open problem in robotics research. This uncertainty is often due to noisy or partial observations of the object…”
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Map quality evaluation for visual localization by Merzic, Hamza, Stumm, Elena, Dymczyk, Marcin, Siegwart, Roland, Gilitschenski, Igor

“…A variety of end-user devices involving keypoint-based mapping systems are about to hit the market e.g. as part of smartphones, cars, robotic platforms, or…”
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Shaping Belief States with Generative Environment Models for RL by Gregor, Karol, Rezende, Danilo Jimenez, Besse, Frederic, Wu, Yan, Merzic, Hamza, Oord, Aaron van den

“…When agents interact with a complex environment, they must form and maintain beliefs about the relevant aspects of that environment. We propose a way to…”
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Scaling Instructable Agents Across Many Simulated Worlds by SIMA Team, Raad, Maria Abi, Ahuja, Arun, Barros, Catarina, Besse, Frederic, Bolt, Andrew, Bolton, Adrian, Brownfield, Bethanie, Buttimore, Gavin, Cant, Max, Chakera, Sarah, Chan, Stephanie C. Y, Clune, Jeff, Collister, Adrian, Copeman, Vikki, Cullum, Alex, Dasgupta, Ishita, de Cesare, Dario, Di Trapani, Julia, Donchev, Yani, Dunleavy, Emma, Engelcke, Martin, Faulkner, Ryan, Garcia, Frankie, Gbadamosi, Charles, Gong, Zhitao, Gonzales, Lucy, Gupta, Kshitij, Gregor, Karol, Hallingstad, Arne Olav, Harley, Tim, Haves, Sam, Hill, Felix, Hirst, Ed, Hudson, Drew A, Hudson, Jony, Hughes-Fitt, Steph, Rezende, Danilo J, Jasarevic, Mimi, Kampis, Laura, Ke, Rosemary, Keck, Thomas, Kim, Junkyung, Knagg, Oscar, Kopparapu, Kavya, Lawton, Rory, Lampinen, Andrew, Legg, Shane, Lerchner, Alexander, Limont, Marjorie, Liu, Yulan, Loks-Thompson, Maria, Marino, Joseph, Cussons, Kathryn Martin, Matthey, Loic, Mcloughlin, Siobhan, Mendolicchio, Piermaria, Merzic, Hamza, Mitenkova, Anna, Moufarek, Alexandre, Oliveira, Valeria, Oliveira, Yanko, Openshaw, Hannah, Pan, Renke, Pappu, Aneesh, Platonov, Alex, Purkiss, Ollie, Reichert, David, Reid, John, Richemond, Pierre Harvey, Roberts, Tyson, Ruscoe, Giles, Elias, Jaume Sanchez, Sandars, Tasha, Sawyer, Daniel P, Scholtes, Tim, Simmons, Guy, Slater, Daniel, Soyer, Hubert, Strathmann, Heiko, Stys, Peter, Tam, Allison C, Teplyashin, Denis, Terzi, Tayfun, Vercelli, Davide, Vujatovic, Bojan, Wainwright, Marcus, Wang, Jane X, Wang, Zhengdong, Wierstra, Daan, Williams, Duncan, Wong, Nathaniel, York, Sarah, Young, Nick

“…Building embodied AI systems that can follow arbitrary language instructions in any 3D environment is a key challenge for creating general AI. Accomplishing…”
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Probing Emergent Semantics in Predictive Agents via Question Answering by Das, Abhishek, Carnevale, Federico, Merzic, Hamza, Rimell, Laura, Schneider, Rosalia, Abramson, Josh, Hung, Alden, Ahuja, Arun, Clark, Stephen, Wayne, Gregory, Hill, Felix

“…Recent work has shown how predictive modeling can endow agents with rich knowledge of their surroundings, improving their ability to act in complex…”
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Creating Multimodal Interactive Agents with Imitation and Self-Supervised Learning by DeepMind Interactive Agents Team, Abramson, Josh, Ahuja, Arun, Brussee, Arthur, Carnevale, Federico, Cassin, Mary, Fischer, Felix, Georgiev, Petko, Goldin, Alex, Gupta, Mansi, Harley, Tim, Hill, Felix, Humphreys, Peter C, Hung, Alden, Landon, Jessica, Lillicrap, Timothy, Merzic, Hamza, Muldal, Alistair, Santoro, Adam, Scully, Guy, von Glehn, Tamara, Wayne, Greg, Wong, Nathaniel, Yan, Chen, Zhu, Rui

“…A common vision from science fiction is that robots will one day inhabit our physical spaces, sense the world as we do, assist our physical labours, and…”
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Causally Correct Partial Models for Reinforcement Learning by Rezende, Danilo J, Danihelka, Ivo, Papamakarios, George, Ke, Nan Rosemary, Jiang, Ray, Weber, Theophane, Gregor, Karol, Merzic, Hamza, Viola, Fabio, Wang, Jane, Mitrovic, Jovana, Besse, Frederic, Antonoglou, Ioannis, Buesing, Lars

“…In reinforcement learning, we can learn a model of future observations and rewards, and use it to plan the agent's next actions. However, jointly modeling…”
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Vision for Bosnia and Herzegovina in Artificial Intelligence Age: Global Trends, Potential Opportunities, Selected Use-cases and Realistic Goals by Ajanović, Zlatan, Aličković, Emina, Branković, Aida, Delalić, Sead, Kurtić, Eldar, Malikić, Salem, Mehonić, Adnan, Merzić, Hamza, Šehić, Kenan, Trbalić, Bahrudin

“…Artificial Intelligence (AI) is one of the most promising technologies of the 21. century, with an already noticeable impact on society and the economy. With…”
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