Publications related to Tangent functional connectomes uncover more unique phenotypic traits

Exploring dynamic functional connectivity by incorporating prior knowledge of brain structure

The synchronized firing of distant neuronal populations gives rise to a wide array of functional brain networks that underlie human brain function. Given the enormous perception, learning, and cognition potential of the human brain, it is not surprising th ...

EPFL2020

On maximum volume submatrices and cross approximation for symmetric semidefinite and diagonally dominant matrices

Daniel Kressner, Stefano Massei, Alice Cortinovis

The problem of finding a k x k submatrix of maximum volume of a matrix A is of interest in a variety of applications. For example, it yields a quasi-best low-rank approximation constructed from the rows and columns of A. We show that such a submatrix can a ...

ELSEVIER SCIENCE INC2020

Regression Networks for Meta-Learning Few-Shot Classification

Matthias Grossglauser, Arnout Jan J Devos

We propose regression networks for the problem of few-shot classification, where a classifier must generalize to new classes not seen in the training set, given only a small number of examples of each class. In high dimensional embedding spaces the directi ...

2020

A Brief History of Simulation Neuroscience

Henry Markram, Xue Fan

Our knowledge of the brain has evolved over millennia in philosophical, experimental and theoretical phases. We suggest that the next phase is simulation neuroscience. The main drivers of simulation neuroscience are big data generated at multiple levels of ...

FRONTIERS MEDIA SA2019

MATHICSE Technical Report : On maximum volume submatrices and cross approximation for symmetric semidefinite and diagonally dominant matrices

Daniel Kressner, Stefano Massei, Alice Cortinovis

The problem of finding a

k\times k

submatrix of maximum volume of a matrix A is of interest in a variety of applications. For example, it yields a quasi-best low-rank approximation constructed from the rows and columns of A. We show that such a submatrix ...

MATHICSE2019

Multi-panel, on-single-chip Memristive Biosensing

Giovanni De Micheli, Sandro Carrara, Danilo Demarchi, Ioulia Tzouvadaki, Abuduwaili Tuoheti

Memristive biosensors have demonstrated excellent capabilities for ultrasensitive bio-detection. In the present work, memristive biosensing chips are designed, fabricated and implemented in a for the first time presented multi-panel on-chip detection for d ...

2019

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Body posture can greatly influence human performance when carrying out manipulation tasks. Adopting an appropriate pose helps us regulate our motion and strengthen our capability to achieve a given task. This effect is also observed in robotic manipulation ...

2018

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BACKGROUND: 22q11.2 deletion syndrome (22q11DS) is the third-largest known genetic risk factor for the development of psychosis. Dysconnectivity has consistently been implicated in the physiopathology of psychosis. Structural covariance of cortical morphol ...

2018

Accelerated Stochastic Matrix Inversion: General Theory and Speeding up BFGS Rules for Faster Second-Order Optimization

Sebastian Urban Stich

We present the first accelerated randomized algorithm for solving linear systems in Euclidean spaces. One essential problem of this type is the matrix inversion problem. In particular, our algorithm can be specialized to invert positive definite matrices i ...

2018

Accelerated Stochastic Matrix Inversion: General Theory and Speeding up BFGS Rules for Faster Second-Order Optimization

Sebastian Urban Stich

We present the first accelerated randomized algorithm for solving linear systems in Euclidean spaces. One essential problem of this type is the matrix inversion problem. In particular, our algorithm can be specialized to invert positive definite matrices i ...

NEURAL INFORMATION PROCESSING SYSTEMS (NIPS)2018

Tangent functional connectomes uncover more unique phenotypic traits

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Exploring dynamic functional connectivity by incorporating prior knowledge of brain structure

On maximum volume submatrices and cross approximation for symmetric semidefinite and diagonally dominant matrices

Regression Networks for Meta-Learning Few-Shot Classification

A Brief History of Simulation Neuroscience

MATHICSE Technical Report : On maximum volume submatrices and cross approximation for symmetric semidefinite and diagonally dominant matrices

Multi-panel, on-single-chip Memristive Biosensing

Accelerated Stochastic Matrix Inversion: General Theory and Speeding up BFGS Rules for Faster Second-Order Optimization

Accelerated Stochastic Matrix Inversion: General Theory and Speeding up BFGS Rules for Faster Second-Order Optimization

Exploring dynamic functional connectivity by incorporating prior knowledge of brain structure

A Brief History of Simulation Neuroscience

Regression Networks for Meta-Learning Few-Shot Classification

MATHICSE Technical Report : On maximum volume submatrices and cross approximation for symmetric semidefinite and diagonally dominant matrices

Multi-panel, on-single-chip Memristive Biosensing

Accelerated Stochastic Matrix Inversion: General Theory and Speeding up BFGS Rules for Faster Second-Order Optimization

On maximum volume submatrices and cross approximation for symmetric semidefinite and diagonally dominant matrices

Accelerated Stochastic Matrix Inversion: General Theory and Speeding up BFGS Rules for Faster Second-Order Optimization