Beyond worst-case analysis, with or without predictions

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A de facto standard approach in solving computer vision tasks is to use a common high-resolution camera and choose its placement on an agent based on human intuition. On the other hand, extremely simple and well-designed visual sensors found throughout nat ...

We develop a model-free approach to optimally control stochastic, Markovian systems subject to a reach-avoid constraint. Specifically, the state trajectory must remain within a safe set while reaching a target set within a finite time horizon. Due to the t ...

The application of kernel-based Machine Learning (ML) techniques to discrete choice modelling using large datasets often faces challenges due to memory requirements and the considerable number of parameters involved in these models. This complexity hampers ...

Two design studios were successively taught in two schools of architecture: one at the Harvard Graduate School of Design (GSD) and the other at the Swiss Federal Institute of Technology in Lausanne (EPFL) in Lausanne, Switzerland, based on "A Global Morato ...

Recent progress in computer vision has been driven by a simple yet transformative observation: the potential of 30-year-old neural networks can be unlocked by massively scaling their parameters and the amount of human-labeled training data. This breakthrou ...

Clustering in education, particularly in large-scale online environments like MOOCs, is essential for understanding and adapting to diverse student needs. However, the effectiveness of clustering depends on its interpretability, which becomes challenging w ...

High-entropy alloys (HEAs), containing several metallic elements in near-equimolar proportions, have long been of interest for their unique mechanical properties. More recently, they have emerged as a promising platform for the development of novel heterog ...

Machine learning has provided a means to accelerate early-stage drug discovery by combining molecule generation and filtering steps in a single architecture that leverages the experience and design preferences of medicinal chemists. However, designing mach ...

Superconducting electronics provide us with cryogenic digital circuits that can rival established technologies in performance and energy consumption. Today, the lack of tools for the design of large-scale integrated superconducting circuits is a major obst ...

The official Spherical Tokamak for Energy Production mission aims to demonstrate the ability to generate net electricity from fusion with the STEP Prototype Power plant. One of the key technological and engineering challenges in fusion power plants is mana ...

Non-convex constrained optimization problems have become a powerful framework for modeling a wide range of machine learning problems, with applications in k-means clustering, large- scale semidefinite programs (SDPs), and various other tasks. As the perfor ...

This paper presents the cooling concept for a medium voltage modular multilevel converter cell. To optimize power density, the metallic enclosure is used to dissipate the heat generated by semiconductor losses, while maintaining maximum temperatures below ...

Exploring a wide range of relevant design options from the outset is crucial for every sound conceptual design process. Optimization techniques are generally employed to generate well-performing structural design options. However, focusing only on performa ...

Exploring a wide range of design options is crucial for every sound conceptual design process. In the conventional structural design workflow, optimization techniques are generally employed to generate well-performing design options. However, focusing only ...

Structural systems are a significant contributor to buildings’ embodied carbon and reusing structural elements in new load-bearing applications is one strategy to reduce this impact. However, integrating this approach into existing design workflows without ...

Driven by the rising popularity of chatbots such as ChatGPT, there is a budding line of research proposing guidelines for chatbot design, both in general and specifically for digital education. Nevertheless, few researchers have focused on providing concep ...

A design concept is proposed for the building block, a dot, of programmable braille readers utilizing bistable shell buckling, magnetic actuation, and pneumatic loading. The design process is guided by Finite Element simulations, which are initially valida ...

Unsupervised graph representation learning aims to learn low-dimensional node embeddings without supervision while preserving graph topological structures and node attributive features. Previous Graph Neural Networks (GNN) require a large number of labeled ...

The decentralisation and unpredictability of new renewable energy sources require rethinking our energy system. Data-driven approaches, such as reinforcement learning (RL), have emerged as new control strategies for operating these systems, but they have n ...

Novel technologies, fabrication methods, controllers and computational methods are rapidly advancing the capabilities of soft robotics. This is creating the need for design techniques and methodologies that are suited for the multi-disciplinary nature of s ...

Beyond worst-case analysis, with or without predictions

Chat with Graph Search

How Far Can a 1-Pixel Camera Go? Solving Vision Tasks Using Photoreceptors and Computationally Designed Visual Morphology

A learning-based approach to stochastic optimal control under reach-avoid constraint

Scalable kernel logistic regression with Nyström approximation: Theoretical analysis and application to discrete choice modelling

Teaching Not To

Exploiting Representation Similarities in Self-Supervised Learning for Vision Tasks

Interpret3C: Interpretable Student Clustering Through Individualized Feature Selection

Surface segregation in high-entropy alloys from alchemical machine learning

Machine learning-aided generative molecular design

Technology-Aware Logic Synthesis for Superconducting Electronics

Models implemented in the methodological approach to design the initial STEP first wall contour

Augmented Lagrangian Methods for Provable and Scalable Machine Learning

Thermal Design of a Medium Voltage Modular Multilevel Converter Cell

Computational Conceptual Design – Typological Exploration Of Spatial Truss Systems Through Optimization

Computational conceptual design — typological exploration of spatial truss systems through optimization

Interactive design with optimum matchmaking of reused structural elements – a software implementation

TRACE: A Conceptual Model to Guide the Design of Educational Chatbots

Leveraging the Snap Buckling of Bistable Magnetic Shells to Design a Refreshable Braille Dot

Unsupervised Graph Representation Learning with Cluster-aware Self-training and Refining

Reinforcement Learning for Joint Design and Control of Battery-PV Systems

The science of soft robot design: A review of motivations, methods and enabling technologies