Concept

Inductive reasoning

Related publications (30)

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

The ability to reason, plan and solve highly abstract problems is a hallmark of human intelligence. Recent advancements in artificial intelligence, propelled by deep neural networks, have revolutionized disciplines like computer vision and natural language ...

EPFL2024

VolRecon: Volume Rendering of Signed Ray Distance Functions for Generalizable Multi-View Reconstruction

Sabine Süsstrunk, Tong Zhang, Yufan Ren

The success of the Neural Radiance Fields (NeRF) in novel view synthesis has inspired researchers to propose neural implicit scene reconstruction. However, most existing neural implicit reconstruction methods optimize perscene parameters and therefore lack ...

2024

The impact of different methods of increasing the intensity of compassion in engineering ethics cases

Roland John Tormey, Nihat Kotluk

Despite the growing interest in emotions in engineering education, empirical research on incorporating them into engineering ethics education is limited. Therefore, we designed this experimental study to assess how different methods for integrating compass ...

2024

Integrated Wireless Power, Data Communication, and Thermal Sensing System for Autonomous Multisite Brain Implants

Mohammad Javad Karimi

Implanted medical devices (IMDs) have been widely developed to support the monitoring and recording of biological data inside the body or brain. Wirelessly powered IMDs, a subset of implantable electronics, have been proposed to eliminate the limitations r ...

EPFL2024

Generalization and Personalization of Machine Learning for Multimodal Mobile Sensing in Everyday Life

Lakmal Buddika Meegahapola

A range of behavioral and contextual factors, including eating and drinking behavior, mood, social context, and other daily activities, can significantly impact an individual's quality of life and overall well-being. Therefore, inferring everyday life aspe ...

EPFL2024

Data-Driven Music Theory: Curating and Investigating Large Corpora of Digitally Encoded Music Analyses

Johannes Hentschel

This dissertation on data-driven music theory is centered around curatorial practices concerning the creation, publication, and evaluation of large, expert-annotated symbolic datasets. With its primary interest in the harmony of European tonal music from i ...

EPFL2024

The inductive bias of deep learning: Connecting weights and functions

Guillermo Ortiz Jimenez

Years of a fierce competition have naturally selected the fittest deep learning algorithms. Yet, although these models work well in practice, we still lack a proper characterization of why they do so. This poses serious questions about the robustness, trus ...

EPFL2023

Language Model Decoding as Likelihood–Utility Alignment

Boi Faltings, Robert West, Maxime Jean Julien Peyrard, Debjit Paul, Valentin Hartmann, Martin Josifoski, Frano Rajic, Jiheng Wei

A critical component of a successful language generation pipeline is the decoding algorithm. However, the general principles that should guide the choice of a decoding algorithm re- main unclear. Previous works only compare decoding algorithms in narrow sc ...

Assoc Computational Linguistics-Acl2023

Monotonicity Reasoning in the Age of Neural Foundation Models

Zeming Chen

The recent advance of large language models (LLMs) demonstrates that these large-scale foundation models achieve remarkable capabilities across a wide range of language tasks and domains. The success of the statistical learning approach challenges our unde ...

Springer2023

Climatic Affinities or Type As A Structure Of Relations, Based On Typological Transfer In The Work Of Lacaton & Vassal And Other Similar Precedents

Tiago André Pratas Borges

It is a generally accepted idea that typology is an essential element in the disciplinary dimension of architecture. The concept of typology, in its most common definition, is sufficiently malleable to cover a wide range of uses, but it is also this vaguen ...

2023

Climatic Affinities or Type As A Structure Of Relations Based On Typological Transfer In The Work Of Lacaton & Vassal And Other Similar Precedents

Tiago André Pratas Borges

2023

Keep Sensors in Check: Disentangling Country-Level Generalization Issues in Mobile Sensor-Based Models with Diversity Scores

Daniel Gatica-Perez, Lakmal Buddika Meegahapola

Machine learning models trained with passive sensor data from mobile devices can be used to perform various inferences pertaining to activity recognition, context awareness, and health and well-being. Prior work has improved inference performance through t ...

Assoc Computing Machinery2023

CLIP the Gap: A Single Domain Generalization Approach for Object Detection

Mathieu Salzmann, Martin Pierre Engilberge, Vidit Vidit

Single Domain Generalization (SDG) tackles the problem of training a model on a single source domain so that it generalizes to any unseen target domain. While this has been well studied for image classification, the literature on SDG object detection remai ...

Ieee Computer Soc2023

Federated Learning under Covariate Shifts with Generalization Guarantees

Volkan Cevher, Grigorios Chrysos, Fanghui Liu, Thomas Michaelsen Pethick

This paper addresses intra-client and inter-client covariate shifts in federated learning (FL) with a focus on the overall generalization performance. To handle covariate shifts, we formulate a new global model training paradigm and propose Federated Impor ...

Journal of Machine Learning Research Inc.2023

Learning Robust and Adaptive Representations: from Interactions, for Interactions

Yuejiang Liu

Interactions are ubiquitous in our world, spanning from social interactions between human individuals to physical interactions between robots and objects to mechanistic interactions among different components of an intelligent system. Despite their prevale ...

EPFL2023

Higher Order Asymptotics: Applications to Satellite Conjunction and Boundary Problems

Soumaya Elkantassi

Higher-order asymptotics provide accurate approximations for use in parametric statistical modelling. In this thesis, we investigate using higher-order approximations in two-specific settings, with a particular emphasis on the tangent exponential model. ...

EPFL2023

Interventionist estimands in event history analysis

Matias Janvin

The presence of competing events, such as death, makes it challenging to define causal effects on recurrent outcomes. In this thesis, I formalize causal inference for recurrent events, with and without competing events. I define several causal estimands an ...

EPFL2023

Space Oddity? A Statistical Formulation of Conjunction Assessment

Anthony Christopher Davison, Soumaya Elkantassi

Satellite conjunctions involving "near misses" of space objects are becoming increasingly likely. One approach to risk analysis for them involves the computation of the collision probability, but this has been regarded as having some counterintuitive prope ...

AMER INST AERONAUTICS ASTRONAUTICS2022

Generalization and Personalization of Mobile Sensing-Based Mood Inference Models: An Analysis of College Students in Eight Countries

Daniel Gatica-Perez, Lakmal Buddika Meegahapola

Mood inference with mobile sensing data has been studied in ubicomp literature over the last decade. This inference enables context-aware and personalized user experiences in general mobile apps and valuable feedback and interventions in mobile health apps ...

ASSOC COMPUTING MACHINERY2022

Cognitive twin construction for system of systems operation based on semantic integration and high-level architecture

Dimitrios Kyritsis, Jinzhi Lu

With the increasing complexity of engineered systems, digital twins (DTs) have been widely used to support integrated modeling, simulation, and decision-making of the system of systems (SoS). However, when integrating DTs of each constituent system, it is ...

IOS PRESS2022