EVA: An Encrypted Vector Arithmetic Language and Compiler for Efficient Homomorphic Computation

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With recent innovations in artificial intelligence (AI), machines can now recognize architectural patterns and generate new forms in ways that far exceed human capacity. The integration of machines in the design process has ushered in a substantial shift i ...

Recent developments in neural architecture search (NAS) emphasize the significance of considering robust architectures against malicious data. However, there is a notable absence of benchmark evaluations and theoretical guarantees for searching these robus ...

Formally verifying the correctness of software is necessary to merit the trust people put in software systems. Currently, formal verification requires human effort to prove that a piece of code matches its specification and code changes to improve verifiab ...

In this work, we demonstrate the utility of state representation learning applied to modeling the time evolution of electron density and temperature profiles at ASDEX-Upgrade (AUG). The proposed model is a deep neural network, which learns to map the high ...

Graph-based representation approaches have been proven to be successful in the analysis of biomedical data due to their capability of capturing intricate dependencies between biological entities, such as the spatial organization of different cell types in ...

In this paper, we present a new parameterization and optimization procedure for minimizing the weight of ribbed plates. The primary goal is to reduce embodied CO2 in concrete floors as part of the effort to diminish the carbon footprint of the construction ...

Photometric stereo, a computer vision technique for estimating the 3D shape of objects through images captured under varying illumination conditions, has been a topic of research for nearly four decades. In its general formulation, photometric stereo is an ...

Distributed constraint optimization (DCOP) is a framework in which multiple agents with private constraints (or preferences) cooperate to achieve a common goal optimally. DCOPs are applicable in several multi-agent coordination/allocation problems, such as ...

A method for optimizing at least one of a geometry, an implantation procedure, and/or stimulation protocol of one or more electrodes for an electrical stimulation of a target structure in a nervous system of a living being by a computer device, the method ...

Electrical stimulation of the visual nervous system could improve the quality of life of patients affected by acquired blindness by restoring some visual sensations, but requires careful optimization of stimulation parameters to produce useful perceptions. ...

Advances in computational capabilities and large volumes of experimental data have established computer simulations of brain tissue models as an important pillar in modern neuroscience. Alongside, a variety of domain specific languages (DSLs) have been dev ...

Compilers assure that any produced optimized code is semantically equivalent to the original code. However, even "correct" compilers may introduce security bugs as security properties go beyond translation correctness. Security bugs introduced by such corr ...

The prospect of massive parallelism of optics enabling fast and low energy cost operations is attracting interest for novel photonic circuits where 3-dimensional (3D) implementations have a high potential for scalability. Since the technology for data inpu ...

During the Artificial Intelligence (AI) revolution of the past decades, deep neural networks have been widely used and have achieved tremendous success in visual recognition. Unfortunately, deploying deep models is challenging because of their huge model s ...

This paper examines how the European press dealt with the no-vax reactions against the Covid-19 vaccine and the dis- and misinformation associated with this movement. Using a curated dataset of 1786 articles from 19 European newspapers on the anti-vaccine ...

The 70-kD heat shock protein (Hsp70) chaperone system is a central hub of the proteostasis network that helps maintain protein homeostasis in all organisms. The recruitment of Hsp70 to perform different and specific cellular functions is regulated by the J ...

In this thesis, we reveal that supervised learning and inverse problems share similar mathematical foundations. Consequently, we are able to present a unified variational view of these tasks that we formulate as optimization problems posed over infinite-di ...

Type-level programming is becoming more and more popular in the realm of functional programming. However, the combination of type-level programming and subtyping remains largely unexplored in practical programming languages. This paper presents match types ...

While road obstacle detection techniques have become increasingly effective, they typically ignore the fact that, in practice, the apparent size of the obstacles decreases as their distance to the vehicle increases. In this letter, we account for this by c ...

Codebook-based optimizations are a class of algorithmic-level transformations able to effectively reduce the computing and memory requirements of Convolutional Neural Networks (CNNs). This approach tightly limits the number of unique weights in each layer, ...

EVA: An Encrypted Vector Arithmetic Language and Compiler for Efficient Homomorphic Computation

Chattez avec Graph Search

Deep Architectural Form

Robust NAS under adversarial training: benchmark, theory, and beyond

Automated Formal Verification of Software Network Functions

On learning latent dynamics of the AUG plasma state

Tertiary Lymphoid Structures Generation Through Graph-Based Diffusion

Mesh-based topology, shape and sizing optimization of ribbed plates

Aggregating Spatial and Photometric Context for Photometric Stereo

Differentially private multi-agent constraint optimization

A method and system for optimizing design, implantation, and stimulation protocols of electrodes stimulating the nervous system

Decoding electroencephalographic responses to visual stimuli compatible with electrical stimulation

MOD2IR: High-Performance Code Generation for a Biophysically Detailed Neuronal Simulation DSL

Silent Bugs Matter: A Study of Compiler-Introduced Security Bugs

From 3D to 2D and back again

Improving the Training of Compact Neural Networks for Visual Recognition

Examining European Press Coverage of the Covid-19 No-Vax Movement: An NLP Framework

Data-driven large-scale genomic analysis reveals an intricate phylogenetic and functional landscape in J-domain proteins

Optimization Over Banach Spaces: A Unified View on Supervised Learning and Inverse Problems

Type-Level Programming with Match Types

Perspective Aware Road Obstacle Detection

An Accuracy-Driven Compression Methodology to Derive Efficient Codebook-Based CNNs