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Found 12 papers, 12 papers with code
Should we be going MAD? A Look at Multi-Agent Debate Strategies for LLMs
In this context, multi-agent debate (MAD) has emerged as a promising strategy for enhancing the truthfulness of LLMs.
Winner Takes It All: Training Performant RL Populations for Combinatorial Optimization
Applying reinforcement learning (RL) to combinatorial optimization problems is attractive as it removes the need for expert knowledge or pre-solved instances.
Universally Expressive Communication in Multi-Agent Reinforcement Learning
Allowing agents to share information through communication is crucial for solving complex tasks in multi-agent reinforcement learning.
Reinforcement Learning for Branch-and-Bound Optimisation using Retrospective Trajectories
By retrospectively deconstructing the search tree into multiple paths each contained within a sub-tree, we enable the agent to learn from shorter trajectories with more predictable next states.
Learning to Solve Combinatorial Graph Partitioning Problems via Efficient Exploration
Compared to the nearest competitor, ECORD reduces the optimality gap by up to 73% on 500 vertex graphs with a decreased wall-clock time.
Autoregressive neural-network wavefunctions for ab initio quantum chemistry
In recent years, neural network quantum states (NNQS) have emerged as powerful tools for the study of quantum many-body systems.
Learning Group Structure and Disentangled Representations of Dynamical Environments
Learning disentangled representations is a key step towards effectively discovering and modelling the underlying structure of environments.
Backpropagation through nonlinear units for all-optical training of neural networks
Backpropagation through nonlinear neurons is an outstanding challenge to the field of optical neural networks and the major conceptual barrier to all-optical training schemes.
Emerging Technologies Signal Processing Optics
Exploratory Combinatorial Optimization with Reinforcement Learning
Our approach of exploratory combinatorial optimization (ECO-DQN) is, in principle, applicable to any combinatorial problem that can be defined on a graph.
Pushing Purcell-enhancement beyond its limits
It is found that birefringence can mitigate the tradeoff between stronger emitter-cavity coupling and efficient photon extraction.
Quantum Physics
Polarisation oscillations in birefringent emitter-cavity systems
We present the effects of resonator birefringence on the cavity-enhanced interfacing of quantum states of light and matter, including the first observation of single photons with a time-dependent polarisation state that evolves within their coherence time.
Quantum Physics
Nonlinear Zeeman Effects in the Cavity-Enhanced Emission of Polarised Photons
We theoretically and experimentally investigate nonlinear Zeeman effects within a polarised single-photon source that uses a single 87Rb atom strongly coupled to a high finesse optical cavity.
Quantum Physics
