Publications related to Direct Prediction of 3D Body Poses from Motion Compensated Sequences

Efficient Temporally-Aware DeepFake Detection using H.264 Motion Vectors

Sabine Süsstrunk, Yufan Ren, Peter Arpad Grönquist, Alessio Verardo, Qingyi He

Video DeepFakes are fake media created with Deep Learning (DL) that manipulate a person’s expression or identity. Most current DeepFake detection methods analyze each frame independently, ignoring inconsistencies and unnatural movements between frames. Som ...

2024

Machine learning models for prediction of electrochemical properties in supercapacitor electrodes using MXene and graphene nanoplatelets

Mohammad Khaja Nazeeruddin

Herein, machine learning (ML) models using multiple linear regression (MLR), support vector regression (SVR), random forest (RF) and artificial neural network (ANN) are developed and compared to predict the output features viz. specific capacitance (Csp), ...

Lausanne2024

On distributional autoregression and iterated transportation

Victor Panaretos, Laya Ghodrati

We consider the problem of defining and fitting models of autoregressive time series of probability distributions on a compact interval of Double-struck capital R. An order-1 autoregressive model in this context is to be understood as a Markov chain, where ...

Hoboken2024

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Paul Scharnhorst

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

EPFL2024

Random matrix methods for high-dimensional machine learning models

Antoine Philippe Michel Bodin

In the rapidly evolving landscape of machine learning research, neural networks stand out with their ever-expanding number of parameters and reliance on increasingly large datasets. The financial cost and computational resources required for the training p ...

EPFL2024

Distributional Regression and Autoregression via Optimal Transport

Laya Ghodrati

We present a framework for performing regression when both covariate and response are probability distributions on a compact and convex subset of

\R^d

. Our regression model is based on the theory of optimal transport and links the conditional Fr'echet m ...

EPFL2023

Bayes-optimal Learning of Deep Random Networks of Extensive-width

Florent Gérard Krzakala, Lenka Zdeborová, Hugo Chao Cui

We consider the problem of learning a target function corresponding to a deep, extensive-width, non-linear neural network with random Gaussian weights. We consider the asymptotic limit where the number of samples, the input dimension and the network width ...

2023

Advanced Interaction-aware Motion Models for Motorcycle Trajectory Prediction: Experiments on pNEUMA Datasets

Jingran Su

Forecasting the motion of motorcycles is a critical task for an autonomous system deployed in complex traffic, considering its distinguished characteristics compared to other vehicles. Motion of motorcycles in a scene is governed by the traffic context, i. ...

2023

From finger animation to full-body embodiment of avatars with different morphologies and proportions

Mathias Guy Delahaye

VR (Virtual Reality) is a real-time simulation that creates the subjective illusion of being in a virtual world.This thesis explores how integrating the user's body and fingers can be achieved and beneficial for the user to experience VR.At the advent of V ...

EPFL2023

Processing load, and not stimulus evidence, determines the duration of unconscious visual feature integration

Michael Herzog, Leila Drissi Daoudi - Kleinbauer, Lukas Vogelsang

Integration across space and time is essential for the analysis of motion, low contrast, and many more stimuli. A crucial question is what determines the duration of integration. Based on classical models of decision-making, one might expect that integrati ...

2023

Direct Prediction of 3D Body Poses from Motion Compensated Sequences

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Efficient Temporally-Aware DeepFake Detection using H.264 Motion Vectors

Machine learning models for prediction of electrochemical properties in supercapacitor electrodes using MXene and graphene nanoplatelets

On distributional autoregression and iterated transportation

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Random matrix methods for high-dimensional machine learning models

Distributional Regression and Autoregression via Optimal Transport

Bayes-optimal Learning of Deep Random Networks of Extensive-width

Advanced Interaction-aware Motion Models for Motorcycle Trajectory Prediction: Experiments on pNEUMA Datasets

From finger animation to full-body embodiment of avatars with different morphologies and proportions

Processing load, and not stimulus evidence, determines the duration of unconscious visual feature integration

Efficient Temporally-Aware DeepFake Detection using H.264 Motion Vectors

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Machine learning models for prediction of electrochemical properties in supercapacitor electrodes using MXene and graphene nanoplatelets

On distributional autoregression and iterated transportation

Random matrix methods for high-dimensional machine learning models

Bayes-optimal Learning of Deep Random Networks of Extensive-width

Distributional Regression and Autoregression via Optimal Transport

Advanced Interaction-aware Motion Models for Motorcycle Trajectory Prediction: Experiments on pNEUMA Datasets

From finger animation to full-body embodiment of avatars with different morphologies and proportions

Processing load, and not stimulus evidence, determines the duration of unconscious visual feature integration