Канал: ADASE Group

Bayesian ML (2021). Lecture 10: Bayesian Neural Networks

Bayesian ML (2021). Lecture 10: Bayesian Neural Networks

Bayesian ML (2021). Lecture 7: Approximate Bayesian Inference

Bayesian ML (2021). Lecture 7: Approximate Bayesian Inference

Bayesian ML (2021). Seminar 7: Mean field approximation. Bayesian GMM

Bayesian ML (2021). Seminar 7: Mean field approximation. Bayesian GMM

Bayesian ML (2021). Seminar 10: Bayesian Neural Networks

Bayesian ML (2021). Seminar 10: Bayesian Neural Networks

Bayesian ML (2021). Lecture 9: Generative Models. VAE

Bayesian ML (2021). Lecture 9: Generative Models. VAE

Bayesian ML (2021). Seminar 9: Implementing Vanilla VAE, IWAE, and VQ-VAE

Bayesian ML (2021). Seminar 9: Implementing Vanilla VAE, IWAE, and VQ-VAE

Bayesian ML (2021). Lecture 3: Relevance Vector Machine

Bayesian ML (2021). Lecture 3: Relevance Vector Machine

Bayesian ML (2021). Seminar 3

Bayesian ML (2021). Seminar 3

Bayesian ML (2021). Lecture 2: Conjugate Distributions. Bayesian Linear Regression

Bayesian ML (2021). Lecture 2: Conjugate Distributions. Bayesian Linear Regression

Bayesian ML (2021). Seminar 2

Bayesian ML (2021). Seminar 2

Bayesian ML (2021). Lecture 1: Bayesian Machine Learning. Use Cases.

Bayesian ML (2021). Lecture 1: Bayesian Machine Learning. Use Cases.

Bayesian ML (2021). Seminar 1

Bayesian ML (2021). Seminar 1

Addressing Cold Start in Recommender Systems with Hierarchical Graph Neural Networks

Addressing Cold Start in Recommender Systems with Hierarchical Graph Neural Networks

Graph Neural Network for Model Selection using Time Series Data

Graph Neural Network for Model Selection using Time Series Data

ADASE Research Fair 2020-2021

ADASE Research Fair 2020-2021

Deep Vectorization of Technical Drawings

Deep Vectorization of Technical Drawings

WEEK 2 - Day 3 - Foundations of Data Science - Parallelization and Large Scale ML in Python

WEEK 2 - Day 3 - Foundations of Data Science - Parallelization and Large Scale ML in Python

WEEK 2 - Day 2 - Foundations of Data Science - Antipatterns in Python

WEEK 2 - Day 2 - Foundations of Data Science - Antipatterns in Python

WEEK 2 - Day 1 - Foundations of Data Science - Packages & Modules in Python

WEEK 2 - Day 1 - Foundations of Data Science - Packages & Modules in Python

WEEK 1 - Day 2 - Foundations of Data Science - Software Engineering for Data Science

WEEK 1 - Day 2 - Foundations of Data Science - Software Engineering for Data Science

WEEK 1 - Day 3 - Foundations of Data Science - Software Engineering for Data Science

WEEK 1 - Day 3 - Foundations of Data Science - Software Engineering for Data Science

WEEK 1 - Day 1 - Foundations of Data Science - Software Engineering for Data Science

WEEK 1 - Day 1 - Foundations of Data Science - Software Engineering for Data Science

Classification of Single-Lead Electrocardiograms: TDA Informed Machine Learning

Classification of Single-Lead Electrocardiograms: TDA Informed Machine Learning

Adaptive Partitioning for Template Functions on Persistence Diagrams

Adaptive Partitioning for Template Functions on Persistence Diagrams

Persistent Homology Machine Learning for Fingerprint Classification

Persistent Homology Machine Learning for Fingerprint Classification

Chatter Diagnosis in Milling using Supervised Learning and Topological Features Vector

Chatter Diagnosis in Milling using Supervised Learning and Topological Features Vector

Adaptive Template System: Data-Driven Feature Selection for Learning with Persistence Diagrams

Adaptive Template System: Data-Driven Feature Selection for Learning with Persistence Diagrams

Bayesian Topological Learning for Brain State Classification

Bayesian Topological Learning for Brain State Classification

Path Homologies of Deep Networks

Path Homologies of Deep Networks

Exposition and Interpretation of the Topology of Neural Networks

Exposition and Interpretation of the Topology of Neural Networks

A Notion of Harmonic Clustering in Simplicial Complexes

A Notion of Harmonic Clustering in Simplicial Complexes

Multiscale Geometric Data Analysis via Laplacian Eigenvector Cascading

Multiscale Geometric Data Analysis via Laplacian Eigenvector Cascading

Mapper Based Classifier

Mapper Based Classifier

Hyperparameter Optimization of Topological Features for Machine Learning Applications

Hyperparameter Optimization of Topological Features for Machine Learning Applications

MLSS19 - Testimonials: Sam Kessler

MLSS19 - Testimonials: Sam Kessler

MLSS19 - Testimonials: Gang Li

MLSS19 - Testimonials: Gang Li

MLSS19 - Testimonials: Galina Baimeeva

MLSS19 - Testimonials: Galina Baimeeva

MLSS19 - Testimonials: Johannes Oberreuter & Jesus Luque

MLSS19 - Testimonials: Johannes Oberreuter & Jesus Luque

MLSS19 - Testimonials: Kimberlin Van Wijnen & Emilio Jorge

MLSS19 - Testimonials: Kimberlin Van Wijnen & Emilio Jorge

MLSS19 - Testimonials: Lachlan Mason

MLSS19 - Testimonials: Lachlan Mason

MLSS19 - Testimonials: Sayantan Sengupta

MLSS19 - Testimonials: Sayantan Sengupta

MLSS19 - Testimonials: Sara Garcia

MLSS19 - Testimonials: Sara Garcia

MLSS19 - Testimonials: Laurie Prelot

MLSS19 - Testimonials: Laurie Prelot

MLSS19 - Testimonials: Maria Kiourlappou

MLSS19 - Testimonials: Maria Kiourlappou

MLSS19 - Testimonials: Jennifer Williams

MLSS19 - Testimonials: Jennifer Williams

MLSS19 - Testimonials: Alexandre Voisin

MLSS19 - Testimonials: Alexandre Voisin

MLSS19 - Testimonials: Lior Yariv & Ana Gerós

MLSS19 - Testimonials: Lior Yariv & Ana Gerós

MLSS19 - Testimonials: Raphael Labaca Castro

MLSS19 - Testimonials: Raphael Labaca Castro

MLSS19 - Testimonials: Daria Babaeva

MLSS19 - Testimonials: Daria Babaeva

MLSS19 - Testimonials: Ramaseshan Kannan

MLSS19 - Testimonials: Ramaseshan Kannan

MLSS19 - Testimonials: Adil Salim

MLSS19 - Testimonials: Adil Salim

MLSS19 - Testimonials: Roberto Leyva Fernandez

MLSS19 - Testimonials: Roberto Leyva Fernandez

MLSS19 - Testimonials: Roufaida Laidi

MLSS19 - Testimonials: Roufaida Laidi

MLSS19 - Testimonials: Elise van der Pol & Michela Massi

MLSS19 - Testimonials: Elise van der Pol & Michela Massi

Discussion Group - Robust Learning of Trimmed Estimators via Manifold Sampling

Discussion Group - Robust Learning of Trimmed Estimators via Manifold Sampling

Discussion Group - Differential Dynamic Programming for Structured Prediction and Attention

Discussion Group - Differential Dynamic Programming for Structured Prediction and Attention

Discussion Group - Using Mode Connectivity for Loss Landscape Analysis

Discussion Group - Using Mode Connectivity for Loss Landscape Analysis