IBM Heron
PulseAugur coverage of IBM Heron — every cluster mentioning IBM Heron across labs, papers, and developer communities, ranked by signal.
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Quantum GAN advances AI-driven drug design with fewer parameters
Researchers have developed a novel latent style-based Quantum Wasserstein GAN (QGAN) designed to accelerate and improve the efficiency of de novo drug design. This hybrid quantum-classical model combines a variational a…
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Quantum Hamiltonian Embeddings Framework Introduced for Supervised Learning
Researchers have introduced a novel supervised learning framework called quantum Hamiltonian embeddings, which encodes classical datasets into a parameterized Hamiltonian. The framework optimizes this data-dependent Ham…
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Quantum-Native Language Models Explored with Dissipative Memory
Researchers have developed trainable quantum-native language models that utilize quantum registers for their hidden states and learn token-conditioned quantum channels. These models aim to generate next-byte probabiliti…
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AI Startup VIDRAFT Tapped for Quantinuum Quantum Computing Access
Korean AI startup VIDRAFT has been selected as an enterprise user of Quantinuum's quantum computing platform, indicating a move towards quantum-classical hybrid approaches in AI development. VIDRAFT has demonstrated pri…
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QANTIS quantum belief updates achieve 32 steps on IBM Heron
The QANTIS quantum belief update system has demonstrated the ability to maintain accuracy across 32 planning steps on IBM's Heron quantum hardware. This system successfully updated beliefs without altering the course of…
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QANTIS system uses quantum processors for belief updates on IBM Heron
Researchers have developed QANTIS, a system that utilizes quantum processors as a calibrated belief-update service for autonomous systems operating under partial observability. This approach aims to provide a posterior …
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Entanglement, not parameters, governs quantum policy generalization
A new research paper proposes that entanglement, rather than the number of parameters, is the key factor determining generalization in quantum reinforcement learning policies. The study introduces a PAC-Bayesian framewo…
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Graph RL router boosts quantum circuit fidelity using calibration data
Researchers have developed a new quantum circuit routing method using graph reinforcement learning that incorporates calibration data from quantum processors. This approach, trained with proximal policy optimization and…
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Quantum Circuit Routing Enhanced by Calibration-Aware Reinforcement Learning
Researchers have developed a novel routing method for quantum circuits that incorporates calibration data to improve fidelity. This graph reinforcement learning approach uses same-day calibration information from IBM He…
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Quantum kernel analysis reveals unified pathology in quantum GPs
Researchers have developed a new diagnostic tool to analyze quantum Gaussian process kernels, revealing that seemingly unrelated issues in quantum machine learning are governed by the same underlying quantity: the norma…