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17 results

Centre for Quantum Technologies
QTML 2025: Variational quantum algorithms with exact geodesic transport

Authors: André Ferreira-Martins, Renato M. S. Farias, Giancarlo Camilo, Thiago O. Maciel, Allan Tosta, Ruge Lin, Abdulla Alhajri, ...

18:23
QTML 2025: Variational quantum algorithms with exact geodesic transport

0 views

8 hours ago

Image Processing, CV, ML, DL & AI Projects
Image Denoising | Variational Bayes | Gaussian–GMRF Prior | Mean-Field Factorization | Python

Image Denoising | Variational Bayes Approximation | Gaussian–GMRF Prior | Mean-Field Factorization | Python Welcome to ...

0:24
Image Denoising | Variational Bayes | Gaussian–GMRF Prior | Mean-Field Factorization | Python

0 views

21 hours ago

Centre for Quantum Technologies
QTML 2025: Do You Know What Q-Means?

Authors: Arjan Cornelissen, Joao F. Doriguello, Alessandro Luongo and Ewin Tang Abstract: Clustering is one of the most ...

26:45
QTML 2025: Do You Know What Q-Means?

0 views

8 hours ago

Ali Bereyhi
IntroML @ ECE-UofT - Lecture 2: Deterministic and Probabilistic Clustering

We get back to K-means clustering algorithm. This time we define the underlying learning problem through risk formulation.

1:19:20
IntroML @ ECE-UofT - Lecture 2: Deterministic and Probabilistic Clustering

8 views

16 hours ago

Practical stats
Understanding the Standard Error of Regression (SER): How Wrong is Your Model?

Welcome to a deep dive into one of the most practical tools in statistics and data science: the Standard Error of the Regression ...

4:15
Understanding the Standard Error of Regression (SER): How Wrong is Your Model?

0 views

14 hours ago

Centre for Quantum Technologies
QTML 2025: Decoded Quantum Interferometry

Authors: Stephen Jordan, Noah Shutty, Mary Wootters, Adam Zalcman, Alexander Schmidhuber, Robbie King, Sergei Isakov, ...

30:42
QTML 2025: Decoded Quantum Interferometry

0 views

8 hours ago

Centre for Quantum Technologies
QTML 2025: A Bit of Freedom Goes a Long Way: Quantum and Classical Algorithms for Online Learning

Full Title: A Bit of Freedom Goes a Long Way: Quantum and Classical Algorithms for Online Learning of MDPs under a Generative ...

29:40
QTML 2025: A Bit of Freedom Goes a Long Way: Quantum and Classical Algorithms for Online Learning

3 views

8 hours ago

BTech Junction
Lec 13 | Vertex Cover Problem | Theory of Computation (TOC) | BTech 3rd Year

... widely used in network security, optimization, resource allocation, and approximation algorithms. This lecture is useful for B.Sc., ...

30:48
Lec 13 | Vertex Cover Problem | Theory of Computation (TOC) | BTech 3rd Year

47 views

7 hours ago

Practical stats
Fitted Values vs. Residuals: Actual ($y$) vs. Predicted ($\hat{y}$) Explained Simply

If you've ever wondered how a computer "learns" to predict house prices or stock trends, you are actually looking at the interaction ...

5:00
Fitted Values vs. Residuals: Actual ($y$) vs. Predicted ($\hat{y}$) Explained Simply

0 views

20 hours ago

Dr Mohit
Analytical Methods vs. Numerical Methods

In this video, we briefly compare Analytical Methods and Numerical Methods. We explain what each method means, how ...

8:42
Analytical Methods vs. Numerical Methods

43 views

19 hours ago

Jeffrin Santon
Just Coding

Coding Graph Approximator and Competitive programming.

43:31
Just Coding

1 view

Streamed 1 day ago

Murad Sultan Ezouidi Hsm : Pioneers In Maths
Use EMST's approach for solving polynomials of degree (n=8)

The provided research paper introduces Ezouidi's Theorem, a mathematical framework designed to solve high-degree ...

6:32
Use EMST's approach for solving polynomials of degree (n=8)

0 views

22 hours ago

Murad Sultan Ezouidi Hsm : Pioneers In Maths
Use EMST's approach for solving polynomials of degree (n= 8)

The provided research paper introduces Ezouidi's Theorem, a mathematical framework designed to solve high-degree ...

6:28
Use EMST's approach for solving polynomials of degree (n= 8)

0 views

22 hours ago

Emergent Mind
Maximum Mean Discrepancy: How to Compare High-Dimensional Data

This video explores Maximum Mean Discrepancy (MMD), a robust statistical framework that allows data scientists to determine if ...

2:10
Maximum Mean Discrepancy: How to Compare High-Dimensional Data

0 views

22 hours ago

Murad Sultan Ezouidi Hsm : Pioneers In Maths
Use EMST's approach for solving polynomials of degree (n= 8)

The provided research paper introduces Ezouidi's Theorem, a mathematical framework designed to solve high-degree ...

6:32
Use EMST's approach for solving polynomials of degree (n= 8)

0 views

22 hours ago

Vlad Turlo
OptiMat Chat: Revolutionizing Materials Discovery with Atomistic Simulations and AI

Step into the era of Software 3.0, where human language becomes the code for advanced materials discovery. OptiMat Chat is an ...

2:47
OptiMat Chat: Revolutionizing Materials Discovery with Atomistic Simulations and AI

7 views

23 hours ago

Emergent Mind
Liquid Neural Networks: When AI Mimics Nature's Flow (1811.00321)

Paper: Liquid Time-constant Recurrent Neural Networks as Universal Approximators (1811.00321) Published: 1 Nov 2018.

2:13
Liquid Neural Networks: When AI Mimics Nature's Flow (1811.00321)

0 views

1 day ago