Proof pending. Core topic summary fields are still materializing.
Topic-specific paper and score movement from the daily diff ledger.
Oscillations and synchronization are widely believed to play a fundamental role in representation and computation. However, existing machine learning approaches based on synchronization dynamics have ...
We introduce mlx-snn, the first spiking neural network (SNN) library built natively on Apple's MLX framework. As SNN research grows rapidly, all major libraries -- snnTorch, Norse, SpikingJelly, Lava ...
Mixture-of-Experts (MoE) architectures have emerged as a powerful paradigm for scaling neural networks while maintaining computational efficiency. However, standard MoE implementations rely on two rig...
Backpropagation algorithm has driven the remarkable success of deep neural networks, but its lack of biological plausibility and high computational costs have motivated the ongoing search for alternat...
In this paper an attractor FCM is created, tested, and analyzed. This FCM is neither a hebbian based nor agentic, nor a hybrid; it rather is a gradient descent based, physics constrained, Jacobian ver...
Freshness
Canonical route: /topics
Agent Handoff
Canonical ID neural-networks | Route /topic/neural-networks
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/topic/neural-networksMCP example
{
"tool": "search_papers",
"arguments": {
"query": "Neural Networks",
"cluster": "Neural Networks"
}
}source_context
{
"surface": "topic",
"mode": "topic",
"query": "Neural Networks",
"normalized_query": "neural-networks",
"route": "/topic/neural-networks",
"paper_ref": null,
"topic_slug": "neural-networks",
"benchmark_ref": null,
"dataset_ref": null
}Use This Via API or MCP
Topic pages bundle paper counts, viability trends, author concentration, and top questions into one canonical surface your agents can reference before they open Signal Canvas or create a workspace.