Neural networks and fuzzy systems

QTML 2025: Accelerating Inference for Multilayer Convolutional Neural Networks

QTML 2025: A Unified Theory of Quantum Neural Network Loss Landscape

Generative AI L17: BiRNNs and Stacked Deep RNNs

Generative AI L16: LSTMs

Deep Learning 2 [Even Semester 2025/2026 Telyu] - Multilayer Perceptrons & Neural Network

MLP Live session

Le "Q-Day" approche ... et PERSONNE n'est prêt.

The "Q-Day" is approaching ... and NO ONE is ready.

[Generative AI in Urdu/Hindi] Lecture 17: Transformers (first pass)

MLP Live session Week 4

They solved AI hallucinations!

Keynote- Neural Race Reduction Dynamics of feature learning in deep architectures (Prof Andrew Saxe)

Deep Learning 1 [Even Semester 2025/2026 Telyu] - Introduction to Deep Learning

Lorin Crawford - When more isn't better: Rethinking Scale in Single-cell Foundation Models

Is AI Hiding Its Full Power? With Geoffrey Hinton

Awni Altabaa: Unlocking Out-of-Distribution Generalization in Transformers via Latent Reasoning

MLP Live session | Week 3 Session 2

[Generative AI in Urdu/Hindi] Lecture 15: Methods of computing attention

Beyond the Buzzwords: How Neural Networks Actually Learn

[ИАД, весна 2026] Введение в машинное обучение. Лекция 3: Нейронные сети

[IAD, Spring 2026] Introduction to Machine Learning. Lecture 3: Neural Networks

Renier Mendoza: Image reconstruction in electrical impedance tomography using deep neural networks

Pantelis Vlachas: Hypernetworks for Adaptive and Generalizable Forecasting in Dynamical Systems

Masanobu Horie: Structure-Preserving Graph Neural Networks: Enforcing Symmetry and Conservation Laws

Luca Galimberti: Infinite-dimensional Deep Learning methods for Finance

Krishnan Raghavan: The role of architecture in learning a continuum of task

Florian Rossmannek: Echo states and fading memory in state-space systems

Deepseek Sparse Attention

Wei Kang: Deep Learning for Data Assimilation

MLP Live session | Week 3

Benjamin Charles Walker: Linear Neural Controlled Differential Equations

Masanobu Inubushi: Reservoir computing with generalized readout based on generalized synchronization

Grok 4.2 est intelligent … mais genre SUPER INTELLIGENT !

Grok 4.2 is smart … but like SUPER SMART!

MLP Live session | Week 2

Graph Sample and Aggregate: GraphSAGE

Graph Neural Networks: what are they?

Graph Neural Networks: message passing

Graph Convolutional Networks

Graph Attention Networks (GAT)

[Generative AI in Urdu/Hindi] Lecture 13: LSTMs, bi-directional, multi-layer, teacher forcing.

MLP Live session | Week 2

[Generative AI in Urdu/Hindi] Lecture 12: RNN variations, its issues, possible solutions. LSTMs.