Symmetry Compositions
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Related Articles from SNS
Symmetries Here and There, Combined Everywhere: Cross-space Symmetry Compositions in Robotics
arXiv:2605.22639v2 Announce Type: replace Abstract: Robots exhibit a rich variety of symmetries arising from their mechanical structure and the properties of their tasks. Although many robotics problems exhibit several symmetries simultaneously, existing approaches typically treat them in isolation, failing to exploit their combined potential. This paper introduces cross-space symmetry compositions, a framework for learning robot policies that are jointly equivariant to multiple symmetries...
Explaining a probabilistic prediction on the simplex with Shapley compositions
arXiv:2408.01382v3 Announce Type: replace Abstract: Originating in game theory, Shapley values are widely used for explaining a machine learning model's prediction by quantifying the contribution of each feature's value to the prediction. This requires a scalar prediction as in binary classification, whereas a multiclass probabilistic prediction is a discrete probability distribution, living on a multidimensional simplex. In such a multiclass setting the Shapley values are typically computed...
Minimal essential requirements for neural tube self-organisation
The reliable generation of diverse cell types in precise proportions is essential for the formation of functional tissues during embryonic development. Three-dimensional organoid models derived from pluripotent stem cells (PSCs) provide powerful systems for identifying principles governing tissue self-organisation. Neural tube organoids (NTOs), initiated from single PSCs with a pulse of retinoic acid (RA), self-organise into structures containing floorplate cells that secrete SHH morphogen...
Composite B-Spline Current Deposition and Interpolation Operators for Thin-Wire Finite-Difference Time-Domain Simulations
arXiv:2605.21450v3 Announce Type: replace Abstract: Holland-Simpson thin-wire finite-difference time-domain (FDTD) simulations of obliquely oriented closed-loop antennas exhibit persistent low-frequency parasitic currents because the current-deposition operator fails to conserve charge. This deposition operator, together with an interpolation operator that samples the tangential electric field along the wire, can be realized as regularizations of distributions: the wire current is deposited...
A Padding Method for Enhanced Encoding of Inorganic Structures with Varying Chemical Compositions
arXiv:2605.30743v1 Announce Type: cross Abstract: Designing novel inorganic materials through generative models remains an important challenge for material science, driven by the complexity and diversity of inorganic structures across expansive chemical compositions and structural landscape. The vast combinatorial space of inorganic compounds demands innovative, AI-driven approaches to overcome limitations in generative accuracy and efficiency.
A Padding Method for Enhanced Encoding of Inorganic Structures with Varying Chemical Compositions
arXiv:2605.30743v2 Announce Type: replace-cross Abstract: Designing novel inorganic materials through generative models remains an important challenge for material science, driven by the complexity and diversity of inorganic structures across expansive chemical compositions and structural landscape. The vast combinatorial space of inorganic compounds demands innovative, AI-driven approaches to overcome limitations in generative accuracy and efficiency.
Multilayer Babinet metamaterial to initiate nonreciprocal topological phenomena and generalized Faraday rotation
new Abstract: Multilayers of Babinet complementary periodic structures constructed with miniarrays of spherical plasmonic nanoresonators were optimized to ensure Generalized Faraday Rotation. Nonreciprocal rotation and asymmetric transmission were achieved in spectrally overlapping regions due to the reach physics involving (i) symmetry breaking via coupled localized modes, (ii) Brillouin zone-folding stemmed from constituent sub-lattices forming in-plane twisted coupled loops, (iii)...
The KNN rollercoaster: from bulk ceramics to phase engineered wafer-scale thin films
Announce Type: cross Abstract: Since the initial disclosure of the extraordinary piezoelectric coefficients of Potassium sodium niobate (KNN) in near-equimolar bulk ceramics, its development trajectory has resembled a rollercoaster, with its integration into microelectronics severely lagging due to thermodynamic stability issues and poor planar process compatibility. In this work, we revisit the bulk-derived phase diagram for the specific case of thin films integrated on silicon. By...
Exact equivariance, kept through training, buys zero-shot generalisation across the symmetry group
arXiv:2606.03003v1 Announce Type: new Abstract: A latent world model built from an equivariant encoder $E$ and an equivariant predictor $f$ inherits a provable symmetry of its training loss: when the world's dynamics genuinely carries a group $G$ acting on latents by an orthogonal representation $\rho(g)$, the one-step prediction relMSE is exactly invariant across the whole group, so fitting the dynamics on a restricted slice of orientations mathematically determines it on the entire orbit...
Deep learning four decades of human migration
Abstract Human migration is a fundamental driver of global demographic change, shaping population structure, labour markets and social policy across countries1,2,3. Although long-term migration patterns are often linked to economic development4, they can shift rapidly in response to shocks such as conflict, environmental crises and political change5. Despite its importance, migration remains difficult to measure consistently: existing data are sparse, concentrated in high-income settings and...