Neuronal Dynamics From single neurons to networks and models of cognition Wulfram Gerstner, Werner M. Kistler, Richard Naud and Liam Paninski What happens in our brain when we make a decision? What triggers a neuron to send out a signal? What is the neural code? This textbook for advanced undergraduate and beginning graduate students provides a thorough and up-to-date introduction to the fields of
Membrane protein analogues could accelerate drug discoveryNewsResearch EPFL researchers have created a deep learning pipeline for designing soluble analogues of key protein structures used in pharmaceutical development, sidestepping the prohibitive cost of extracting these proteins from cell membranes.
The VPI the interface with industrial milieus, in particular through the EPFL Innovation Park, a place of interaction and proximity between companies and the campus. Introduction For more than 20 years, EPFL has been a key player in innovation in Switzerland. The Vice Presidency for Innovation is dedicated to this role and, in particular, to the development of platforms for interaction between EPF
1 Sort vs. Hash Join Revisited for Near-Memory Execution Nooshin Mirzadeh, Onur Kocberber,�� Babak Falsafi, Boris Grot Emerging technology § Stacked memory: A logic die w/ a stack of DRAM dies § Makes near-memory processing practical Why NMP? § Less data movement à Less energy consumption § Leverage DRAM's massive internal BW & parallelism à High performance Exploit NMP to accelerate key alg
Abstract We introduce a novel Deep Network architecture that implements the full feature point handling pipeline, that is, detection, orientation estimation, and feature description. While previous works have successfully tackled each one of these problems individually, we show how to learn to do all three in a unified manner while preserving end-to-end differentiability. We then demonstrate that
Our research aims at empowering creators. We develop efficient simulation and optimization algorithms to build computational design methodologies for advanced material systems and digital fabrication technologies. Mathematical reasoning, geometric abstractions, and powerful numerical methods are key ingredients in our work. We pursue a holistic approach in that we design and fabricate functional p
About the lab The EPFL DATA lab performs research and teaching at the intersection of systems, programming languages, and theory. We create and study database systems and large-scale data analysis ("big data") systems. On the systems side, our current focus is on building efficient and scalable massively parallel realtime analytics engines. Our technical contributions particularly focus on the opt
The DOT Calculus (Dependent Object Types) Nada Amin Scala Days June 18, 2014 1 DOT: Dependent Object Types I DOT is a core calculus for path-dependent types. I Goals I simplify Scala’s type system by desugaring to DOT I simplify Scala’s type inference by relying on DOT I prove that DOT is type-safe 2 Types in Scala and DOT 3 Types in Scala modular named type scala.collection.BitSet compound type C
Improving OLTP concurrency through Early Lock Release Manos Athanassoulis† manos.athanassoulis@epfl.ch Ryan Johnson†‡ ryan.johnson@epfl.ch Anastasia Ailamaki† anastasia.ailamaki@epfl.ch Radu Stoica† radu.stoica@epfl.ch †Ecole Polytechnique Fédérale de Lausanne Data-Intensive and Applications Laboratory CH-1015, Lausanne ‡Carnegie Mellon University Pittsburgh, PA EPFL-REPORT-152158 ABSTRACT Since t
EPFL scientists have developed a new type of composite thread that varies in stiffness depending on its temperature. Applications range from multifunctional robots to knitted casts, and even tunable medical devices. A new type of thread has been developed at EPFL that varies in stiffness depending on its temperature. This new structure could be used in future robots, orthopedics and even medical d
Mission Data nowadays come in overwhelming volume. In order to cope with this deluge, we explore and use the benefits of geometry and symmetry in higher dimensional data. But volume is not the only problem: data models are also increasingly complex, mixing various components. We thus use redundant dictionaries as a dimensionality reduction tool to dig out information from complicated high-dimensio
LTS2 is a team of researchers led by Prof. Pierre Vandergheynst working within the Institute of Electrical Engineering of the EPFL, one of the two Swiss federal institutes of technology. The main part of our research activities focuses on modern challenges in data processing. The joint expertise of the acoustic group extends the LTS2 research landscape to audio engineering and electroacoustics. —
Focusing on path-dependent types, the paper develops foundations for Scala from first principles. Starting from a simple calculus D-<: of dependent functions, it adds records, intersections and recursion to arrive at DOT, a calculus for dependent object types. The paper shows an encoding of System F with subtyping in D-<: and demonstrates the expressiveness of DOT by modeling a range of Scala cons
リリース、障害情報などのサービスのお知らせ
最新の人気エントリーの配信
処理を実行中です
j次のブックマーク
k前のブックマーク
lあとで読む
eコメント一覧を開く
oページを開く