STFT Phase Retrieval - Robustness and Generative Priors - IPAM at UCLA
Explore STFT phase retrieval, focusing on robustness and generative priors. Learn about stable reconstruction techniques, application of generative models, and reducing required measurements in imaging and acoustics applications.
Splitting the Difference Between Deep and Shallow Solutions of Inverse Problems
Explores balancing compressed sensing and deep learning in computational imaging, showcasing Plenoxels for efficient photorealistic view synthesis without neural networks.
Who Is Responsible for Responsible AI?
Explore ethical considerations and accountability in AI development with Prof. Pascale Fung, addressing crucial questions about responsibility in the field of artificial intelligence.
Versatile Video Coding - Algorithms and Specification
Explore advanced algorithms and specifications for Versatile Video Coding, the latest video compression standard, presented by experts in the field.
Computational Imaging - Deep Learning Approaches
Explore advanced computational imaging techniques with Jong Chul Ye from KAIST, covering innovative approaches in signal processing and image reconstruction.
Heisenberg-Limited Ground State Energy Estimation for Early Fault-Tolerant Quantum Computers
Explore Heisenberg-limited ground state energy estimation for early fault-tolerant quantum computers, featuring a simplified circuit and classical post-processing for improved efficiency.
Bridging the Gap Between Safety and Real-Time Performance for Autonomous Vehicle Control
Explores a novel trajectory planning method for autonomous vehicles, balancing safety and real-time performance through offline computations and runtime optimization to ensure persistent feasibility.
Inverse Problems under a Learned Generative Prior - Lecture 1
Explores inverse problems using generative priors, comparing to sparsity models. Covers theory, algorithms, and applications in compressive sensing and phase retrieval, with focus on deep learning approaches.
Computational Imaging Systems and Optical Design - Webinar
Explore computational imaging systems, diffractive optics, and neural network-based reconstruction in this advanced signal processing webinar by Prof. Wolfgang Heidrich from KAUST.
Physics Matters - In Artificial Intelligence - Natural and Artificial Cognition
Explore natural and artificial cognition, machine learning, and computer vision applications in healthcare, research, and autonomous vehicles with Professor Kalle Åström.
Computational Imaging: Black Hole Shadows and Imaging Algorithms - Webinar
Explore computational imaging techniques for black hole visualization, featuring insights on imaging algorithms, bias avoidance, and telescope design optimization.
Computational Imaging Systems: From DiffuserCam to Neural Activity Tracking - Seminar 2
Explore computational imaging systems, focusing on DiffuserCam technology and its applications in 3D neural activity tracking. Learn about challenges and solutions in image reconstruction and processing.
OpenAI Whisper - Translate and Transcribe Your Video and Audio at Command Line
Comprehensive walkthrough of OpenAI Whisper for multilingual speech recognition, translation, and transcription using command-line interface, with practical demonstrations across various audio formats.
DIY Soil Sensor for Home Assistant Integration
Learn to build and integrate a DIY soil moisture sensor with Home Assistant using ESPHome. Automate your garden watering based on real-time data for efficient plant care and a smarter gardening experience.
The Geometry of Tensors - Carolina Araujo
Explore tensor decomposition, its applications, and geometric interpretation. Learn about recent developments in determining tensor ranks and their significance in various fields.
AI-Guided Nonlinear Optimization for Real-World Problems - IPAM at UCLA
Explore AI-guided optimization techniques for complex real-world problems, focusing on nonconvex objectives and slow-to-evaluate functions in applications like embedding table sharding and antenna design.
Explainable AI to Analyze Internal Decision Mechanism of Deep Neural Networks
Explore techniques for understanding and improving deep neural networks' decision-making processes, focusing on safety in critical applications and automatic correction of unreliable internal nodes.
Model Based Deep Learning with Application to Super Resolution - IPAM at UCLA
Explore model-based deep learning for super-resolution microscopy, merging parametric models with optimization tools to create efficient, interpretable networks from limited training data.
Quantum Fault Tolerance with Flag Qubits - Quantum Colloquium
Explore fault-tolerant quantum computing using flag qubits, a qubit-efficient method for error detection and correction in quantum circuits, with applications and theoretical implications.
Solving Inverse Problems With Deep Neural Networks - Robustness Included?
Exploring robustness of deep learning in inverse problems, focusing on resilience against statistical noise and adversarial perturbations in image reconstruction tasks.
Noise Meter Tutorial - LED Lights and Animation
Create a noise meter with LED lights and Arduino, learning animation techniques and exploring housing options for your project.