📗Papers:
- Witten-type topological field theory of self-organized criticality for stochastic neural networksProvably efficient machine learning for quantum many-body problems
- Normalized Gradient Descent for Variational Quantum Algorithms
- Decoding conformal field theories: from supervised to unsupervised learning
- Tensor networks for unsupervised machine learning
- Quantum-tailored machine-learning characterization of a superconducting qubit
- Overcoming barriers to scalability in variational quantum Monte Carlo
- A tensor network representation of path integrals: Implementation and analysis
- Solving correlation clustering with QAOA and a Rydberg qudit system: a full-stack approach
- Accelerating variational quantum algorithms with multiple quantum processors
- QUBO formulations for system of linear equations
- QFCNN: Quantum Fourier Convolutional Neural Network
- An agnostic-Dolinar receiver for coherent states classification
- A universal duplication-free quantum neural network
- Reinforcement-learning based matterwave interferometer in a shaken optical lattice
- Quantum Brain Networks: a Perspective
- LEAP: Scaling Numerical Optimization Based Synthesis Using an Incremental Approach
- Witten-type topological field theory of self-organized criticality for stochastic neural networks
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