🎫Events:
- On Quantum Linear Algebra for Machine Learning w/ Ewin Tang | March 30 | University of Washington
- IEEE SA Executive Summit on Quantum Computing and Artificial Intelligence |April 7th
- Quantum Education – Workforce Development: Overview of Quantum Machine Learning Algorithms | April 14th
📰News:
- Solving ‘barren plateaus’ is the key to quantum machine learning
- Machine learning shows potential to enhance quantum information transfer
- How and when quantum computers will improve machine learning?
- LANL Researchers Tackle the ‘Barren Plateau’ in Quantum Computing
- QUANTUM AI & QUANTUM BRAIN: THE IMITATION GAME OF THE FUTURE
- AI Gets a Quantum Speed-up
- How Companies Can Utilize AI and Quantum Technologies to Improve Cybersecurity
- Do Alternate Realities Exist? This Artist’s Machines Are Ready to Find Out
📽Videos:
- Machine learning shows potential to enhance quantum information transfer
- QHack 2021: Jules Tilly—Quantum Machine Learning and AI Prospects for Drug Discovery
- Should You Learn Cirq or Qiskit for Quantum Programming?
- Do Large Machine Learning Models Struggle At Maths? and more..
- QHack 2021: Sofia Vallecorsa—Quantum Machine Learning in High Energy Physics: Examples from CERN
- The UK’s Quantum Computer webinar ::: Alexei Kondratyev – Quantum Machine Learning
👨💻Developers;
📗Papers:
- Neural tensor contractions and the expressive power of deep neural quantum states
- Quantum machine learning of graph-structured data
- Parameter Concentration in Quantum Approximate Optimization
- Preparing Bethe Ansatz Eigenstates on a Quantum Computer
- Simulations of state-of-the-art fermionic neural network wave functions with diffusion Monte Carlo
- Federated Quantum Machine Learning
- An Analysis of the Quantum Approximation Optimisation Algorithm
- Effect of constraint and Tabu Search term on Variational Quantum Eigensolver and Subspace-Search Variational Quantum Eigensolver
- Calculation of the ground-state Stark effect in small molecules using the variational quantum eigensolver
- Variational quantum compiling with double Q-learning
- Entangled q-Convolutional Neural Nets
- Quantum Machine Learning with HQC Architectures using non-Classically Simulable Feature Maps
- QuClassi: A Hybrid Deep Neural Network Architecture based on Quantum State Fidelity
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