Institute for Pure & Applied Mathematics (IPAM) Courses

The Role of Data, Precomputation, and Communication in a Quantum Learning Landscape

Explore quantum computing's impact on data analysis, learning from quantum systems, and the interplay between quantum data and computation in distributed systems.

• YouTube
• 48 minutes
• On-Demand
• Free Video

On Quantum Backpropagation and Information Reuse - IPAM at UCLA

Explores quantum backpropagation and information reuse in parameterized quantum models, challenging assumptions about quantum measurement collapse and discussing implications for scaling quantum learning algorithms.

• YouTube
• 35 minutes
• On-Demand
• Free Video

Language Models for Quantum Simulation - IPAM at UCLA

Explore how language models like GPT are revolutionizing quantum simulation, with focus on their application in learning quantum states in Rydberg atom arrays and potential impact on quantum computing.

• YouTube
• 59 minutes
• On-Demand
• Free Video

Learning of Neural Networks with Quantum Computers and Learning of Quantum States with Graphical Models

Explores quantum algorithms for neural network learning and quantum state learning using graphical models, showcasing advancements in computational efficiency and sample complexity for specific quantum states.

• YouTube
• 52 minutes
• On-Demand
• Free Video

Signal and Noise - Learning with Random Quantum Circuits and Other Agents of Chaos

Explores quantum learning in noisy computation, discussing error mitigation limitations and the surprising benefits of non-unital noise in quantum machine learning, challenging conventional understanding.

• YouTube
• 39 minutes
• On-Demand
• Free Video

Training Binary Neural Networks in Quantum Superposition - IPAM at UCLA

Explore quantum hypernetworks for training binary neural networks, unifying parameter, hyperparameter, and architecture optimization in a single quantum-based approach for efficient deep learning deployment.

• YouTube
• 50 minutes
• On-Demand
• Free Video

How to Rethink Quantum Machine Learning - IPAM at UCLA

Explore the intersection of quantum computing and machine learning, challenging conventional approaches and examining core quantum routines from a generalization perspective.

• YouTube
• 43 minutes
• On-Demand
• Free Video

Nathan Wiebe - Quantum Machine Learning

Explore quantum machine learning concepts and applications in this comprehensive lecture by Nathan Wiebe, delving into mathematical aspects and cutting-edge research in the field.

• YouTube
• 1 hour 2 minutes
• On-Demand
• Free Video

Classical Verification of Quantum Learning - IPAM at UCLA

Explore classical verification of quantum learning, discussing interactive proofs, mixture-of-superpositions examples, and scenarios where quantum data enhances or matches classical learning capabilities.

• YouTube
• 52 minutes
• On-Demand
• Free Video

Do Quantum Computers Have Applications in Machine Learning and Combinatorial Optimization

Explores quantum computing's potential in machine learning and optimization, discussing recent developments, comparative power, limitations, and future prospects in these fields.

• YouTube
• 51 minutes
• On-Demand
• Free Video

On Quantum Speedups for Nonconvex Optimization via Quantum Tunneling Walks

Explore quantum speedups for nonconvex optimization using quantum tunneling walks, offering advantages over classical algorithms for problems with high, thin barriers between local minima.

• YouTube
• 55 minutes
• On-Demand
• Free Video

Generating Approximate Ground States of Molecules Using Quantum Machine Learning

Explore quantum machine learning for generating molecular ground states, focusing on potential energy surfaces and efficient state preparation using variational quantum circuits and neural networks.

• YouTube
• 52 minutes
• On-Demand
• Free Video

Learning to Predict Arbitrary Quantum Processes - IPAM at UCLA

Efficient machine learning algorithm for predicting quantum processes, combining state and observable learning techniques. Demonstrates potential for fast prediction of complex quantum dynamics outputs.

• YouTube
• 50 minutes
• On-Demand
• Free Video

Learning Beyond Stabilizer States - IPAM at UCLA

Exploring efficient learning algorithms for quantum states produced by Clifford circuits with T gates, using Bell difference sampling and property testing for stabilizer nullity.

• YouTube
• 46 minutes
• On-Demand
• Free Video

Overview of Learning Structured Quantum States - IPAM at UCLA

Explore efficient methods for learning structured quantum states, focusing on models and classes that require fewer copies for estimation, with insights on Boolean functions and alternative learning approaches.

• YouTube
• 55 minutes
• On-Demand
• Free Video