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Two arXiv papers advance operator learning and TAMP

By PulseAugur Editorial · [2 sources] ·

Two new research papers from arXiv explore advancements in operator learning and task and motion planning. The first paper introduces a novel neural operator architecture that can enforce homogeneous Dirichlet boundary conditions without relying on training data, making it applicable to general geometries and arbitrary mesh data. The second paper presents a system for learning operators in Task and Motion Planning (TAMP) that automatically generates macro-operators, compressing recurring action sequences into single planning steps, which significantly speeds up planning and enables solving longer, more complex tasks. AI

IMPACT These papers contribute to foundational AI research by improving the efficiency and applicability of operator learning and planning systems.

RANK_REASON Two academic papers published on arXiv detailing new methods in operator learning and task and motion planning.

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Two arXiv papers advance operator learning and TAMP

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Two academic papers published on arXiv detailing new methods in operator learning and task and motion planning.
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COVERAGE [2]

  1. arXiv cs.LG TIER_1 English(EN) · Andrew M. Stuart, Margaret Trautner ·

    Enforcing Dirichlet Boundary Conditions in Operator Learning

    arXiv:2608.27256v1 Announce Type: cross Abstract: Operator learning in scientific machine learning is concerned with approximation of maps between infinite-dimensional function spaces; such maps frequently arise as the solution operators of partial differential equations (PDEs). …

  2. arXiv cs.AI TIER_1 English(EN) · Can Emir Bora, Emre Ugur ·

    Macro-Operator Generation and Predicate Selection for TAMP Operator Learning

    arXiv:2608.23629v1 Announce Type: cross Abstract: Creating symbolic operators by hand is one of the main bottlenecks in deploying Task and Motion Planning systems (TAMP). Recent works show that these operators can instead be learned directly from demonstration data. Existing meth…

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