A new multi-hop FiLM approach improves visual reasoning tasks.
problem Challenging multi-modal tasks like visual question-answering and dialogue.
method Generate FiLM layer parameters in a multi-hop fashion, alternating between attending to language and generating parameters.
result Multi-hop FiLM generation achieves state-of-the-art performance on visual dialogue tasks.
Efficient neural models for complex multi-hop reasoning tasks.
problem Complex multi-hop reasoning tasks in large knowledge bases.
method Differentiable neural models using symbolic knowledge bases, with a new operation for multi-hop template construction.
result Simple neural models achieve competitive performance on multi-hop reasoning tasks.
New AI algorithm improves multi-layer optical film design efficiency.
problem Traditional algorithms converge to local optima, limiting global optimal solutions.
method Deep Q-learning for global optimal multi-layer optical film design.
result Deep Q-learning model converges global optimum of optical thin film structure.
In this paper we first review the covering space method with constrained BV functions for solving the classical Plateau's problem. Next, we carefully analyze some interesting examples of soap films compatible with the covering space method: in particular, the case of a soap film only partially wetting a space curve, a …
Solves the film scheduling and staggered showtimes problem for movie theaters.
problem Maximize attendance and revenue by scheduling films with staggered showtimes.
method Binary integer linear optimization to find optimal schedules for each cluster of neighboring locations.
result Optimal scheduling cannot be done for all locations at once, but must be done for each cluster.
A novel beam training scheme optimizes multi-hop THz communications with up to 75% performance gain.
problem Optimizing beam training for multi-hop THz communications with high data rates and low time overhead.
method Developed a reinforcement learning-based hierarchical beam training scheme with dynamic training levels.
result The proposed scheme achieves up to 75% performance gain in spectral efficiency compared to conventional methods.
Method integrates logical rules into neural multi-hop reasoning for drug repurposing.
problem Capturing long-range dependencies in biomedical data.
method Combines logical rules with neural multi-hop reasoning using reinforcement learning.
result Our method outperforms baseline methods in drug repurposing tasks.
In this paper we provide the first examples of non-flat soap films proven to span tetrahedra. These are members of a continuous two parameter family of soap films with tetrahedral boundaries. Of particular interest is a two parameter subfamily where each spanning soap film has the property that two minimal surfaces mee…
Soap films collapse only if their bulk has negative pressure, forming convex shapes.
problem Understanding soap film behavior and collapse conditions.
method Variational analysis of capillarity theory.
result Soap films collapse only if their bulk has negative pressure, forming convex shapes.
Derives equilibrium law for Plateau borders in wet soap films and foams.
problem Equilibrium law for Plateau borders in wet foams and films.
method Rigorous derivation using Gauss' capillarity theory, homotopic spanning condition, and effective compactness theorems.
result Sharp regularity properties of energy minimizers for Plateau borders in wet foams and films.
New method uses multi-hop assortativity to classify network functionalities.
problem Classifying network functionalities based on structure and metadata.
method Introduces multi-hop assortativity to capture node similarity in paths.
result Multi-hop assortativity features outperform state-of-the-art methods in network classification.
We introduce a general-purpose conditioning method for neural networks called FiLM: Feature-wise Linear Modulation. FiLM layers influence neural network computation via a simple, feature-wise affine transformation based on conditioning information. We show that FiLM layers are highly effective for visual reasoning - an…
Extends symmetry and rigidity to surfaces with soap film-like singularities.
problem Symmetry and rigidity of minimal surfaces with singularities.
method Method of moving planes applied to surfaces with Plateau-like singularities.
result Extends classical results to surfaces with singularities.
Study soap films hanging from frames, proving surface limits and curvature conditions.
problem Understanding soap films with gravity and minimal surfaces.
method Compactness theorem for surfaces with vanishing mean curvature and fixed/converging boundaries.
result Minimal surfaces represent all possible limits of almost-minimal surfaces.
We prove existence and a.e. regularity of an area minimizing soap film with a bound on energy spanning a given Jordan curve in R^3. The energy of a film is defined to be the sum of its surface area and the length of its singular branched set. The class of surfaces over which area is minimized includes images of disks, …
A soap film is actually a thin solid fluid bounded by two surfaces of opposite orientation. It is natural to model the film using one polyhedron for each side. Two problems are to get the polyhedra for both sides to be in the same place without canceling each other out and to model triple junctions without introducing …
Develops a geometric framework for soap film instabilities.
problem Soap film instabilities on minimal surfaces.
method Björling representation of minimal surfaces.
result Jacobi fields are maximally localized with lowest eigenfunction amplitude.
GNN-FiLM uses feature-wise linear modulation to improve graph neural networks.
problem Improving graph neural networks for better performance.
method Feature-wise linear modulation applied to target node representations in GNNs.
result GNN-FiLM outperforms baseline methods on a regression task for molecular graphs.
MAGNA improves graph neural networks by incorporating multi-hop context information.
problem Limited context in current graph neural networks.
method Diffuses attention scores across the network, accounting for all paths between nodes.
result State-of-the-art performance on node classification and knowledge graph completion benchmarks.
What are the possible shapes of various things and why? For instance, when a closed wire or a frame is dipped into a soap solution and is raised up from the solution, the surface spanning the wire is a soap film. What are the possible shapes of soap films and why? Or, for instance, why is DNA like a double spiral stair…
Smoothness of collapsed regions in soap films is proven, indicating wetted singularities.
problem Smoothness of collapsed regions in soap films.
method Study of generalized minimizers in capillarity model.
result Collapsed regions are smooth outside of dimensionally small singular sets.
Classifies soap film surfaces with vertical potentials.
problem Classifying soap film surfaces with vertical potentials.
method Variational characterization of n-elastic curves. result Obtains a full description of n-elastic curves. For a given boundary set consisting of arcs and vertices, with two or more arcs meeting at each vertex, we treat the problem of estimating the area density of a soap film-like surface spanning the boundary.
Proposes a framework for private data augmentation in federated learning.
problem Privacy and performance issues in non-IID training datasets.
method Multi-hop federated augmentation with sample compression.
result Significantly improves privacy, transmission delay, and local training performance.
A deep learning algorithm designs low-cost SPP films.
problem Designing SPP films with high accuracy and low cost.
method Guided deep learning algorithm with low-cost sample replacement.
result Deep CNN learns to replace precious metals with ordinary metals, reducing cost.
FiLM improves deep learning for long-term time series forecasting.
problem Preserving historical information without overfitting noise.
method Applies Legendre Polynomials and Fourier projections, adds low-rank approximation.
result Significantly improves multivariate and univariate forecasting accuracy.
We develop a theory of axisymmetric surfaces minimizing a combination of surface tension and nematic elastic energies which may be suitable for describing simple film and bubble shapes. As a function of the elastic constant and the applied tension on the bubbles, we find the analogues of the unduloid, sphere, and nodoi…
Plateau's soap film problem is to find a surface of least area spanning a given boundary. We begin with a compact orientable (n−2)-dimensional submanifold M of Rn. If M is connected, we say a compact set X "spans" M if X intersects every Jordan curve whose linking number with M is 1. Picture a soap fi…
Automated malaria diagnosis from field slides achieves accurate results.
problem Challenges in analyzing field-prepared thin blood film microscopy images.
method Fully automated framework using machine learning, including CNNs trained on diverse field samples.
result Results are close to sufficient for drug resistance monitoring and clinical use-cases.
Improved continual learning method using variational inference and FiLM layers.
problem Training models on new tasks and datasets in an online fashion.
method Generalized Variational Continual Learning (GVCL) with likelihood-tempering and FiLM layers.
result GVCL outperforms existing baselines in both small and large datasets, providing better calibration.
Let M be an n-dimensional complete simply connected Riemannian manifold with sectional curvature bounded above by a nonpositive constant −κ2. Using the cone total curvature TC(Γ) of a graph Γ which was introduced by Gulliver and Yamada Math. Z. 2006, we prove that the density at any point of a soap film-like…
New method finds all thin film structures from reflectometry data.
problem Computational prohibitive for standard algorithms, leading to unreliable analysis.
method Prior-Amortized Neural Posterior Estimation (PANPE) combining simulation-based inference and adaptive priors.
result Identifies all realistic structures in seconds, setting new standards in reflectometry.
Superhighway bypasses data sparsity in cross-domain CF.
problem Data sparsity in cross-domain collaborative filtering.
method Explicit relation-enrichment procedure to enhance cross-domain connectivity.
result Significantly improves recommendation performance in both target and source domains.
New neural KB representation speeds up reasoning with large symbolic knowledge bases.
problem Efficiently reasoning with large symbolic knowledge bases.
method Sparse-matrix reified knowledge base, enabling fully differentiable, scalable neural modules.
result Competitive performance on KB completion and semantic parsing benchmarks.
In mathematics, the classical Plateau problem consists of finding the surface of least area that spans a given rigid boundary curve. A physical realization of the problem is obtained by dipping a stiff wire frame of some given shape in soapy water and then removing it; the shape of the spanning soap film is a solution …
Graph neural networks improve volatility forecasting by capturing spillover effects.
problem Forecasting multivariate realized volatility with spillover effects.
method Customized graph neural networks incorporating spillover effects from multi-hop neighbors.
result Modeling nonlinear spillover effects enhances forecasting accuracy, especially for short-term horizons.
Knowledge base (KB) completion adds new facts to a KB by making inferences from existing facts, for example by inferring with high likelihood nationality(X,Y) from bornIn(X,Y). Most previous methods infer simple one-hop relational synonyms like this, or use as evidence a multi-hop relational path treated as an atomic f…
This paper proves that classical minimal surfaces of arbitrary topological type with total boundary curvature at most 4πmust be smoothly embedded. Related results are proved for varifolds and for soap film surfaces.
FinReflectKG benchmarks financial QA by linking relevant context from a financial KG, improving model performance and efficiency.
problem Efficiently retrieving and navigating relevant financial information across diverse sources and years.
method A benchmark built on a temporally indexed financial KG, generating QA pairs via pattern-specific prompts and quality control, evaluating retrieval scenarios.
result KG-guided retrieval yields substantial gains in correctness and token utilization, improving model performance by 24%.
Langmuir-Blodgett films (LB-films) consist from few LB-monolayers which are high structured nanomaterials that are very promising materials for applications. We use a geometrical approach to describe structurization into LB-monolayers. Consequently, we develop on the 1-jet space J^1([0,\infty),R^2) the single-time Lagr…
Machine learning speeds up FLIM analysis in biomedical research.
problem Complex, slow, and computationally expensive FLIM analysis.
method Machine learning techniques for faster and smarter FLIM data extraction and interpretation.
result Higher accuracy in classifying and segmenting FLIM images compared to conventional methods.
This study compares GNNs and GA-MLPs, finding GA-MLPs can distinguish graphs but not count walks.
problem Comparing expressive power and graph isomorphism testing capabilities of GNNs and GA-MLPs.
method GA-MLPs augment node features with multi-hop operators and apply MLPs node-wise; GNNs are compared as a baseline.
result GA-MLPs can distinguish almost all non-isomorphic graphs but cannot count attributed walks, unlike GNNs.
New task AQA tackles acoustic reasoning from sound scenes.
problem Promote research in acoustic reasoning.
method Generate acoustic scenes from elementary sounds and formulate questions.
result Preliminary results with models FiLM and MAC show promise.
TFiLM expands convolutional models' receptive field with minimal overhead.
problem Capturing long-range dependencies in sequential data.
method A novel architectural component using a recurrent neural network to modulate convolutional model activations.
result TFiLM significantly improves learning speed and accuracy on various tasks.
We derive a new model for pre-strained thin films, which consists of minimizing a biharmonic energy of deformations v∈W2,2 satisfying the Monge-Ampère constraint det∇2v=f. We further discuss multiplicity properties of the minimizers of this model, in some special cases.
Embedding models for entities and relations are extremely useful for recovering missing facts in a knowledge base. Intuitively, a relation can be modeled by a matrix mapping entity vectors. However, relations reside on low dimension sub-manifolds in the parameter space of arbitrary matrices---for one reason, compositio…
TSDS framework reduces edge LLM agent compute by 43%-73% while maintaining safety and reliability.
problem Managing reasoning budget and uncertainty in edge LLM agents.
method Integrates a lightweight convergence probe and a perplexity-based deferral rule calibrated via multi-objective LTT.
result Reduces per-episode thinking compute by 43%-73% over deferral-only baselines.
Multi-hop inference is necessary for machine learning systems to successfully solve tasks such as Recognising Textual Entailment and Machine Reading. In this work, we demonstrate the effectiveness of adaptive computation for learning the number of inference steps required for examples of different complexity and that l…