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#Differentiable Programming

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The Julia Programming Language

NeuroTree - A Differentiable Tree Operator for Tabular Data

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Explore NeuroTree, a differentiable tree operator for tabular data, addressing traditional tree limitations through simultaneous node learning and built-in ensemble techniques.
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1 Lesons
12 minutes
On-Demand
Free-Video
TensorFlow

Swift for TensorFlow - Google I/O 2019

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Explore Swift for TensorFlow, a platform integrating deep neural networks with traditional software development. Learn its benefits for advanced machine learning research and why fast.ai chose it for their deep learning course.
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5 Lesons
28 minutes
On-Demand
Free-Video
Fields Institute

Differentiable Programming for Data-driven Modeling, Optimization, and Control

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Explore data-driven modeling, optimization, and control through differentiable programming techniques in this symposium talk by Jan Drgona from Pacific Northwest National Laboratory.
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1 Lesons
23 minutes
On-Demand
Free-Video
Alan Turing Institute

Learning From Ranks, Learning to Rank - Jean-Philippe Vert, Google Brain

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Explore differentiable approaches to integrate permutations, sorting, and ranking in machine learning, focusing on embedding techniques and relaxation of ranking operators.
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24 Lesons
42 minutes
On-Demand
Free-Video
The Julia Programming Language

A Fast and Flexible CFD Solver with Heterogeneous Execution - JuliaCon 2024

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Explore WaterLily.jl: a fast, flexible CFD solver for CPUs and GPUs. Learn about its meta-programming approach, performance, and potential for ML integration and differentiability.
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1 Lesons
22 minutes
On-Demand
Free-Video
ACM SIGPLAN

Qadence: A Differentiable Interface for Digital-Analog Quantum Programs

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Explore Qadence, a high-level interface for digital-analog quantum programs. Learn about its flexible design, native differentiability, and focus on real device execution for quantum machine learning algorithms.
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1 Lesons
23 minutes
On-Demand
Free-Video
Yannic Kilcher

Gradients Are Not All You Need - Machine Learning Research Paper Explained

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Explores limitations of differentiable programming in machine learning, focusing on chaos-based failures in various systems. Discusses alternatives to backpropagation for gradient estimation in complex, stochastic environments.
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12 Lesons
49 minutes
On-Demand
Free-Video
International Centre for Theoretical Sciences

Differentiable Programming for End-to-end Optimization of Experiments - Lecture 6

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Explore differentiable programming for optimizing experiments in high-energy physics, focusing on end-to-end solutions and advanced machine learning techniques.
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1 Lesons
2 hours 6 minutes
On-Demand
Free-Video
Simons Institute

How Hard Is It to Train Variational Quantum Circuits?

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Explores challenges in training variational quantum circuits, comparing them to classical neural networks and examining quantum generative models, with a focus on robust training methods and circuit compression.
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10 Lesons
29 minutes
On-Demand
Free-Video
Institute for Pure & Applied Mathematics (IPAM)

Tropical Tensor Networks

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Unified tensor network approach for spin glasses using tropical algebra, enabling ground state energy computation, optimal configuration identification, and solution counting. Combines graphical models and quantum circuit simulation.
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15 Lesons
25 minutes
On-Demand
Free-Video
International Centre for Theoretical Sciences

Differentiable Programming for End-to-end Optimization of Experiments - Lecture 5

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Explore differentiable programming for optimizing experiments in high-energy physics. Learn advanced techniques to enhance data analysis and improve experimental design in particle physics research.
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1 Lesons
1 hour 32 minutes
On-Demand
Free-Video
Alan Turing Institute

Generalizing Scientific Machine Learning and Differentiable Simulation Beyond Continuous Models

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Explore advanced scientific machine learning, extending differentiable simulation to complex models like jump diffusions and agent-based systems, addressing challenges in implementation and numerical stability.
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1 Lesons
1 hour 7 minutes
On-Demand
Free-Video
International Centre for Theoretical Sciences

Differentiable Programming for End-to-End Optimization of Experiments - Lecture 7

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Explore differentiable programming for optimizing experiments in high-energy physics. Learn advanced techniques to enhance data analysis and improve experimental design in particle physics research.
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1 Lesons
1 hour 44 minutes
On-Demand
Free-Video
Simons Institute

Machine Learning Gradients in Molecular Simulations

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Explore ML gradients in molecular simulations, including surrogate functions, active learning, and differentiable programming for enhanced scientific modeling and optimization.
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1 Lesons
57 minutes
On-Demand
Free-Video
Simons Institute

Scallop: A Language for Neurosymbolic Programming

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Explore Scallop, a programming language for neurosymbolic learning that combines classical algorithms and deep learning, offering efficient solutions for complex machine learning challenges.
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1 Lesons
35 minutes
On-Demand
Free-Video
Neuro Symbolic

Learning Logical Relationships with Neural Networks - Part 3

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Explore experimental evaluation of Differentiable Inductive Logic Programming for Structured Examples, examining its application in learning logical relationships using neural networks.
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1 Lesons
12 minutes
On-Demand
Free-Video
DataLearning@ICL

Neuromancer: Differentiable Programming Library for Data-driven Modeling and Control

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Explore NeuroMANCER, an open-source library for integrating machine learning with scientific computing, solving optimization problems, and creating differentiable models with physics-based constraints.
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1 Lesons
59 minutes
On-Demand
Free-Video
Alan Turing Institute

NeuroMANCER - Differentiable Programming Library for Data-driven Modeling and Control

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Explore NeuroMANCER: an open-source library for integrating machine learning with scientific computing, focusing on parametric optimization, system identification, and optimal control.
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1 Lesons
1 hour
On-Demand
Free-Video
Inside Livermore Lab

Differentiable Programming for Modeling and Control of Dynamical Systems

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Explore differentiable programming for optimal control of dynamical systems, focusing on differentiable predictive control and its applications in building control and power systems optimization.
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1 Lesons
1 hour 6 minutes
On-Demand
Free-Video