Zobrazeno 1 - 10
of 78
pro vyhledávání: '"Srinivasan, Siddarth"'
Prediction markets elicit and aggregate beliefs by paying agents based on how close their predictions are to a verifiable future outcome. However, outcomes of many important questions are difficult to verify or unverifiable, in that the ground truth
Externí odkaz:
http://arxiv.org/abs/2306.04305
Measurement error mitigation (MEM) techniques are postprocessing strategies to counteract systematic read-out errors on quantum computers (QC). Currently used MEM strategies face a tradeoff: methods that scale well with the number of qubits return ne
Externí odkaz:
http://arxiv.org/abs/2210.12284
Peer reviewed publications are considered the gold standard in certifying and disseminating ideas that a research community considers valuable. However, we identify two major drawbacks of the current system: (1) the overwhelming demand for reviewers
Externí odkaz:
http://arxiv.org/abs/2109.00923
Modeling joint probability distributions over sequences has been studied from many perspectives. The physics community developed matrix product states, a tensor-train decomposition for probabilistic modeling, motivated by the need to tractably model
Externí odkaz:
http://arxiv.org/abs/2010.10653
Autor:
Xu, Liyuan, Chen, Yutian, Srinivasan, Siddarth, de Freitas, Nando, Doucet, Arnaud, Gretton, Arthur
Instrumental variable (IV) regression is a standard strategy for learning causal relationships between confounded treatment and outcome variables from observational data by utilizing an instrumental variable, which affects the outcome only through th
Externí odkaz:
http://arxiv.org/abs/2010.07154
Extending classical probabilistic reasoning using the quantum mechanical view of probability has been of recent interest, particularly in the development of hidden quantum Markov models (HQMMs) to model stochastic processes. However, there has been l
Externí odkaz:
http://arxiv.org/abs/1912.02098
Quantum graphical models (QGMs) extend the classical framework for reasoning about uncertainty by incorporating the quantum mechanical view of probability. Prior work on QGMs has focused on hidden quantum Markov models (HQMMs), which can be formulate
Externí odkaz:
http://arxiv.org/abs/1903.03730
Quantum Graphical Models (QGMs) generalize classical graphical models by adopting the formalism for reasoning about uncertainty from quantum mechanics. Unlike classical graphical models, QGMs represent uncertainty with density matrices in complex Hil
Externí odkaz:
http://arxiv.org/abs/1810.12369
In the Story Cloze Test, a system is presented with a 4-sentence prompt to a story, and must determine which one of two potential endings is the 'right' ending to the story. Previous work has shown that ignoring the training set and training a model
Externí odkaz:
http://arxiv.org/abs/1803.05547
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Chemical Engineering, 2015.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 251-278).
Non-wetting surfaces are characterized by the p
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 251-278).
Non-wetting surfaces are characterized by the p
Externí odkaz:
http://hdl.handle.net/1721.1/98161