Tango*: constrained synthesis planning using chemically informed value functions

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

This paper explores how the dynamics and structure of land ownership can be studied by automating the vectorisation of historical cadastral sources. Our analysis focuses mainly on three cadastres of Lausanne (1722, 1831, 1883). The plans are first georefer ...

Automatic speech recognition (ASR) and spoken language understanding (SLU) is the core component of current voice-powered AI assistants such as Siri and Alexa. It involves speech transcription with ASR and its comprehension with natural language understand ...

Pigeons may transmit diseases to humans and cause damages to buildings, monuments, and other infrastructure. Therefore, several control strategies have been developed, but they have been found to be either ineffective or harmful to animals and often depend ...

Many pathologies cause impairments in the speech production mechanism resulting in reduced speech intelligibility and communicative ability. To assist the clinical diagnosis, treatment and management of speech disorders, automatic pathological speech asses ...

Cortical representations of brief, static stimuli become more invariant to identity-preserving transformations along the ventral stream. Likewise, increased invariance along the visual hierarchy should imply greater temporal persistence of temporally struc ...

Deep neural network (DNN) inference tasks are computationally expensive. Digital DNN accelerators offer better density and energy efficiency than general-purpose processors but still not sufficient to be deployable on resource-constrained settings.Analog c ...

The performance of speaker recognition systems has considerably improved in the last decade. This is mainly due to the development of Gaussian mixture model-based systems and in particular to the use of i-vectors. These systems handle relatively well noise ...

The very shallow geothermal potential (vSGP) is increasingly recognized as a viable resource for providing clean thermal energy in urban and rural areas. This is primarily due to its reliability, low-cost installation, easy maintenance, and little constrai ...

Deep convolutional neural networks have been shown to be vulnerable to arbitrary geometric transformations. However, there is no systematic method to measure the invariance properties of deep networks to such transformations. We propose ManiFool as a simpl ...

We present a Network Address Translator (NAT) written in C and proven to be semantically correct according to RFC 3022, as well as crash-free and memory-safe. There exists a lot of recent work on network verification, but it mostly assumes models of networ ...

Classifiers based on sparse representations have recently been shown to provide excellent results in many visual recognition and classification tasks. However, the high cost of computing sparse representations at test time is a major obstacle that limits t ...

Tango*: constrained synthesis planning using chemically informed value functions

Chat with Graph Search

Revealing the Structure of Land Ownership through the Automatic Vectorisation of Swiss Cadastral Plans

Low-Resource Speech Recognition and Understanding for Challenging Applications

Autonomous Detection and Deterrence of Pigeons on Buildings by Drones

Automatic pathological speech assessment

Temporal stability of stimulus representation increases along rodent visual cortical hierarchies

Analog Neural Networks with Deep-submicron Nonlinear Synapses

Trustworthy speaker recognition with minimal prior knowledge using neural networks

A machine learning approach for mapping the very shallow theoretical geothermal potential

Geometric robustness of deep networks: analysis and improvement

A Formally Verified NAT

Dictionary learning for fast classification based on soft-thresholding