System identifies shifts in sketches for creative drawing.
problem Helping users create more creative sketches.
method Recognizes conceptual shifts between visual categories.
result Produces ambiguous sketches blending features from different categories.
Deep learning model for AI co-creativity boosts design creativity.
problem Design creativity enhancement through AI collaboration.
method Novelty metric applied to deep learning-generated vector representations for conceptual shifts in a co-creative design system.
result Increasing novelty in AI contributions correlates with higher creative outcomes in design.
Dropout improves GAN outputs by preserving input constraints.
problem Generating multiple outputs from one input.
method Using Dropout in GANs to maintain input constraints.
result Enhanced generation of diverse outputs from a single input.
New concept of k-holes in simple drawings and convex drawings.
problem Investigate holes in convex and simple drawings.
method Structural investigation of pseudolinear subdrawings in convex drawings.
result Existence of empty 4-cycles in every simple drawing of K_n.
VQ-DRAW compresses images and generates realistic samples.
problem Learning compact discrete representations of images.
method Sequential discrete VAE with vector quantization.
result VQ-DRAW effectively compresses and generates images.
Rotation systems can't always be drawn in surfaces.
problem Rotation systems and simple drawings in surfaces.
method Extended the plane result to all fixed surfaces.
result Existence of rotation systems not arising from simple drawings in any fixed surface.
We propose a restricted collapsed draw (RCD) sampler, a general Markov chain Monte Carlo sampler of simultaneous draws from a hierarchical Chinese restaurant process (HCRP) with restriction. Models that require simultaneous draws from a hierarchical Dirichlet process with restriction, such as infinite Hidden markov mod…
Examines how meridians and parallels help in map drawing.
problem Understanding map drawing and foliations of the sphere.
method Analyzes Euler's work on cartography and meridians/parallels.
result Meridians and parallels are crucial for map drawing.
Paper generates cartoon giraffes from few original drawings.
problem Creating consistent cartoon sketches with limited data.
method Expressive augmentations and GANs trained on complexity layers.
result Generated sketches are consistent with designer's style.
Study on a bad arm existence checking problem to minimize arm draws.
problem Judging the existence of a positive arm among K given arms.
method Proposes an algorithm with arm selection policy and stopping condition.
result Proves the effectiveness of the proposed algorithm theoretically and empirically.
Criteria found for graph drawings on surfaces.
problem Graph drawings on surfaces.
method Criteria for integer and modulo 2 embeddability.
result Found criteria for graph drawings on surfaces.
We present sketch-rnn, a recurrent neural network (RNN) able to construct stroke-based drawings of common objects. The model is trained on thousands of crude human-drawn images representing hundreds of classes. We outline a framework for conditional and unconditional sketch generation, and describe new robust training …
SPX optimizes multiple graph drawing metrics for better readability.
problem Graph drawing algorithms often optimize one metric at a time, leading to suboptimal layouts.
method Introduces Stress-Plus-X (SPX) framework that optimizes stress, crossings, angles, and upwardness simultaneously.
result SPX achieves results close to state-of-the-art algorithms that optimize metrics individually.
CoSE models complex drawings by treating strokes as a collection that can be composed.
problem Modeling complex free-form structures like diagrams.
method Generative model using autoencoder to project strokes into a fixed latent space, relational model operates in latent space.
result Model captures both individual strokes and their compositional structure.
The Clock Drawing Test (CDT) is a rapid, inexpensive, and popular neuropsychological screening tool for cognitive conditions. The Digital Clock Drawing Test (dCDT) uses novel software to analyze data from a digitizing ballpoint pen that reports its position with considerable spatial and temporal precision, making possi…
There are three main thrusts to this article: a new proof of Levi's Enlargement Lemma for pseudoline arrangements in the real projective plane; a new characterization of pseudolinear drawings of the complete graph; and proofs that pseudolinear and convex drawings of Kn have n2+O(nlogn) and O(n2), respect…
This note provides an elementary proof of the folklore fact that draws from a Dirichlet distribution (with parameters less than 1) are typically sparse (most coordinates are small).
Simplified exposition of graph drawing invariants.
problem Graph drawing invariants and their applications.
method Defining and analyzing a mod2-valued self-intersection invariant.
result Elementary formulations accessible to mathematicians.
Paper finds Dutch Draw optimal baseline for binary classification.
problem Need a proper baseline for binary classification validation.
method Examined all input-independent baseline methods.
result Dutch Draw is optimal baseline under given conditions.
A {\em good drawing\/} of Kn is a drawing of the complete graph with n vertices in the sphere such that: no two edges with a common end cross; no two edges cross more than once; and no three edges all cross at the same point. Gioan's Theorem asserts that any two good drawings of Kn that have the same rotations …
New method learns high-quality Laplacian representations for reinforcement learning.
problem Lack of accurate Laplacian representations in large or continuous state spaces.
method Reformulated spectral graph drawing objective to have eigenvectors as unique global minimizer.
result Learned Laplacian representations more faithfully approximate the ground truth.
A new method for spotting symbols in CAD images reduces annotation costs and improves accuracy.
problem Challenging task of labeling symbols from CAD drawings.
method Pixel-wise point location via Progressive Gaussian Kernels (PGK) and local offset.
result The proposed method achieves good generalization on real-world CAD images.
New bounds show limitations of sample-wise information-theoretic generalization.
problem Limitations of sample-wise information-theoretic generalization bounds.
method Analysis of existing bounds and derivation of new bounds.
result No sample-wise information-theoretic bounds exist for expected squared generalization gap.
CupNet prunes neural nets for cup-shaped data.
problem Pruning neural networks for cup-shaped data.
method Used simulated cup drawing data to prune a neural network.
result Pruning effectively reduces network size for cup-shaped data.
Mathematical analysis shows Delisle-Euler map methods are optimal.
problem Comparing ancient and modern map drawing methods.
method Analyzing similarities and differences between ancient and modern map drawing methods.
result Delisle-Euler map methods are optimal among conical maps.
Can certain shapes be drawn with a pencil and eraser?
problem Characterizing which planar sets can be drawn with a pencil and eraser.
method Analyzes the properties of sets drawable with a pencil and eraser, using open and closed unit disks.
result Drawability cannot be characterized by local obstructions.
Examines parallels between human subjects and texts for causal inference.
problem Ambiguity and fallacies in causal inference using textual data.
method Two strategies: shifting from traits to perceptions and from concepts to parts.
result Highlights the importance of clarifying fundamental concepts.
We usually think of 2-dimensional manifolds as surfaces embedded in Euclidean 3-space. Since humans cannot visualise Euclidean spaces of higher dimensions, it appears to be impossible to give pictorial representations of higher-dimensional manifolds. However, one can in fact encode the topology of a surface in a 1-dime…
JointGAN learns joint distributions across multiple domains.
problem Learning joint distributions across multiple domains.
method Generative adversarial nets (GANs) with multiple generators and a critic, jointly trained.
result Synthesis of draws from full joint distribution.
A grid layout method for graph classification using CNNs.
problem How to project graphs onto grids for CNNs to work effectively.
method Proposes a novel graph-preserving grid layout (GPGL) using integer programming to minimize topological loss, and solves it approximately with a regularized Kamada-Kawai algorithm.
result Demonstrates the success of the method for graph classification using multi-scale maxout CNNs.
Paper proves MDS NP-hard and provides a PTAS.
problem Theoretical limitations of MDS objective function.
method Proves NP-hardness and provides a PTAS approximation algorithm.
result Minimizing Kamada-Kawai objective is NP-hard.
GraphSAC detects anomalies in large graphs by sampling and filtering node subsets.
problem Vulnerability of holistic anomaly detection methods to compromised nodal attributes and network links.
method Randomly draws subsets of nodes, filters out contaminated sets, and uses SSL to estimate nominal label distributions.
result GraphSAC provides performance guarantees and is scalable to large graphs.
New bounds on learning algorithm generalization error derived using information density.
problem Bounding the generalization error of learning algorithms.
method Exponential inequalities and information density/conditional information density.
result Novel bounds on average and tail probability of generalization error.
A new privacy-preserving ML framework using random sampling.
problem Achieving differential privacy in client-distributed ML.
method Draw and Discard: random model sampling for scalability and privacy.
result Demonstrated improved model quality and privacy guarantees.
Sampling more can make models more confident in wrong answers, not better.
problem The modal ceiling and correlation ceiling limit the benefit of increased sampling.
method Analyzes the trade-offs between sampling more and selecting the best answer.
result Extra sampling beyond a certain point does not improve model performance and can even degrade it.
Optimizes tax payments for insurance companies using Lévy risk processes.
problem Maximizing expected accumulated discounted tax payments with a modified objective function.
method Loss-carry-forward tax system applied to spectrally negative Lévy processes until general draw-down time.
result Optimal tax return function and strategy derived.
Here we draw a handlebody picture for the exotic CP^2 # 2(-CP^2) constructed by Akhmedov and Park.
Here we draw a handlebody picture for the exotic CP^2 # 3(-CP^2), constructed by Akhmedov and Park.
Pulli kolam is a ubiquitous art form in south India. It involves drawing a line looped around a collection of dots (pullis) place on a plane such that three mandatory rules are followed: all line orbits should be closed, all dots are encircled and no two lines can overlap over a finite length. The mathematical foundati…
Massively parallel RWS improves inference in complex models.
problem Exponential sample requirement for effective importance weighting.
method Draws K samples of all n latent variables and individually reasons through all combinations. result Significant improvements over standard RWS.
CSP improves time-series forecasting without training, outperforming DeepNPTS in speed and accuracy.
problem Improving probabilistic time-series forecasting without training.
method Mixing empirical and residual draws around a seasonal naive forecast.
result CSP significantly outperforms DeepNPTS on CRPS, normalized mean quantile loss, and coverage metrics.
Detailed study of the financial empirical correlation matrix of the 30 companies comprised by DAX within the period of the last 11 years, using the time-window of 30 trading days, is presented. This allows to clearly identify a nontrivial time-dependence of the resulting correlations. In addition, as a rule, the draw d…
SketchEmbedNet learns image representations from sketches, useful for few-shot learning.
problem Learning image representations from sketches for few-shot learning.
method Training a model to produce sketches of images, focusing on informative embeddings.
result Model produces informative embeddings of novel images, classes, and datasets.
Correct method found for drawing precise envelope of straight lines.
problem Widespread method fails to represent the precise shape of envelope.
method Recently discovered correct method for straight line families in the plane.
result Correct method precisely represents the envelope of straight lines.
In this paper we establish three basic equations for a general soliton structure on the Riemannian manifold (M,<,>). We then draw some geometric conclusions with the aid of the maximum principle.
Pathfinder uses quasi-Newton optimization for variational inference.
problem Approximating complex posterior distributions efficiently.
method Pathfinder combines quasi-Newton optimization with variational methods to approximate log densities.
result Pathfinder produces draws with lower KL divergence than ADVI and comparable to HMC, requiring fewer evaluations.
We establish Bochner-type formulas for operators related to CR automorphisms and spherical CR structures. From such formulas, we draw conclusions about rigidity by making assumptions on the Tanaka-Webster curvature and torsion.
We report on the works of Euler and Chebyshev on the drawing of geographical maps. We point out relations with questions about the fitting of garments that were studied by Chebyshev.