Robo-PlaNet learns robot tasks faster than PlaNet.
problem Training robot tasks with limited or noisy sensor data.
method Asynchronous version of PlaNet that interleaves dynamics model training and data collection.
result Robo-PlaNet achieves higher performance in less time.
Enhances PlaNet for better planning in uncertain environments.
problem Improving deep planning networks for partially observable environments.
method Incorporates Bayesian inference to handle uncertainty in latent models and action candidates.
result Consistently improves asymptotic performance on continuous control tasks.
Study proves rigid spectral properties of planets with metric discontinuities.
problem Establishing spectral rigidity for spherically symmetric planets with discontinuities.
method Novel trace formula applied to two wave types in spherically symmetric manifolds with boundary and interior interfaces.
result Spectral rigidity of spherically symmetric planets with discontinuities is proven.
Model shows consumption growth slows due to finite planet resources.
problem Understanding and predicting consumption growth in a finite planet context.
method Logistic model of consumption growth, cumulant expansion method.
result Social discount rates decline over time due to planetary resource constraints.
Study the geometry of gas giant planets to infer their internal structure.
problem Determine the interior structure of gas giant planets using boundary data.
method Geometric analysis of Riemannian manifolds with conformal blow-up at the boundary.
result The interior structure of a gas giant is uniquely determined by different types of boundary data.
PlaNet learns latent dynamics from images for better planning in unknown environments.
problem Leveraging planning in unknown environments with accurate dynamics models.
method Deep Planning Network (PlaNet) learns dynamics from images using latent space and multi-step variational inference.
result PlaNet achieves high performance in continuous control tasks with contact dynamics and sparse rewards.
We present an algorithm for converting an indoor spherical panorama into a photograph with a simulated overhead view. The resulting image will have an extremely wide field of view covering up to 4π steradians of the spherical panorama. We argue that our method complements the stereographic projection commonly used in t…
Optimizes social interactions for profit, people, and planet using mathematical models.
problem Determining the most effective social configurations for mutual objectives.
method Formulated as a mathematical optimization problem, using (meta)relational models theory.
result Identifies the most suitable combination of sociality forms for mutual objectives.
The study finds the best elliptical trajectory for planets using a variation of the hodograph theorem.
problem Finding the best elliptical trajectory for planets.
method Using a variation of the circular hodograph theorem, the study finds the best fitting ellipse for planetary trajectories by minimizing the sum of square distances from the points to the plane.
result The study finds that the best fitting ellipse for planetary trajectories minimizes the sum of square distances from the points to the plane.
GPRNs accurately model stellar activity affecting RV measurements of exoplanets.
problem Stellar activity limits detection and characterisation of exoplanets.
method Gaussian Process Regression Networks (GPRNs) for joint analysis of RV data and stellar activity indicators.
result GPRNs accurately describe solar RV data, correlating with activity at separations of a few days.
Zero-energy orbits in the Kepler-Heisenberg problem are self-similar and stratify into three families.
problem Determining the motion of a planet around a sun in the Heisenberg group.
method Analysis of the sub-Riemannian Hamiltonian and sub-Laplacian dynamics.
result Zero-energy orbits are self-similar and stratify into future collision, past collision, and quasi-periodic families.
This article presents a theoretical model for a dynamic system based on sustainable development. Due to the relatively absence of theoretical studies and practical issues in the area of sustainable development, Romania aspires to the principles of sustainable development. Based on the concept as a process in which econ…
Residual neural networks improve collision prediction in planetary simulations.
problem Accurate prediction of planetary collisions in N-body simulations.
method Residual neural networks trained on collision data.
result Residual neural networks outperform existing methods in prediction accuracy and generalization.
Bayesian neural network predicts planetary instability.
problem Predicting planetary instability in compact systems.
method Novel Bayesian neural network trained on raw orbital elements.
result Model predicts planetary instability times with high accuracy and robust generalization.
DI-sNMF uses data imputation to separate circumstellar signals in high contrast imaging.
problem Separating circumstellar signals from non-circumstellar signals in high contrast imaging.
method DI-sNMF converts the signal separation problem into a missing data problem, using non-negative matrix factorization to attribute PSF signals to regions flagged as missing data.
result DI-sNMF can precisely measure circumstellar objects without altering them, as shown in simulations and real GPI observations.
The green area of economy is the key of healthy living. It is necessary to convene economic and ecologic framework to establish a market attentive to drastic reduction of emissions damaging our climate and landscapes in rural areas, to the protection of biological diversity of the planet, to stop producing nuclear wast…
CNNs estimate poverty from satellite images, explaining 47% of variation in Mexico.
problem Mapping poverty in developing countries.
method Convolutional Neural Networks trained on high and medium resolution satellite images.
result CNNs explain 47% of poverty variation in Mexico's municipalities.
The purpose of the New York Workshop on Computer, Earth and Space Sciences is to bring together the New York area's finest Astronomers, Statisticians, Computer Scientists, Space and Earth Scientists to explore potential synergies between their respective fields. The 2011 edition (CESS2011) was a great success, and we w…
Simple image augmentation boosts deep RL from pixels.
problem Training deep RL models from raw pixel inputs is challenging.
method Applying standard computer vision data augmentation to reinforcement learning.
result Our method significantly improves SAC's performance on DeepMind control suite.
Defines devices and agents based on behavior, using computational theory.
problem Differentiating between systems described by mechanical and intentional stances.
method Formal definition of devices and agents, using Bayes' rule to calculate subjective probability based on behavior.
result Bayesian approach to distinguishing between mechanical and intentional systems.
System automatically searches for scientific features in Mars rover images.
problem Manual task planning for Mars rover images is time-consuming and error-prone.
method Deep image captioning network and automated task prioritization.
result System can prioritize images for transmission based on search tasks.
Computer program finds flower-like periodic orbits in Kepler-Heisenberg problem.
problem Motion of a planet around a sun in the sub-Riemannian Heisenberg group.
method Monte Carlo optimization with a shooting method and a symplectic integrator.
result Discovery of a family of flower-like periodic orbits with new symmetry types.
Gaussian processes enhance EO with accurate and uncertain predictions.
problem Challenges in GP models for EO, including data-driven physics and causal inference.
method Data-driven physics-aware models respecting signal characteristics and physical laws.
result GP models need to evolve for better EO applications.
DISTANA improves weather prediction by inferring hidden factors from temperature data.
problem Inferring hidden factors in spatiotemporal processes without supervision.
method Enhanced DISTANA architecture for spatiotemporal data, active tuning for latent state inference.
result DISTANA achieves more accurate predictions than other methods, inferring hidden factors from temperature data.
Detects and maps informal settlements using satellite data.
problem Mapping informal settlements for aid distribution.
method Combining satellite data and machine learning for roofing material detection.
result Effective aid distribution through accurate settlement mapping.
AI enhances microbiology and microbiome research through machine learning.
problem Understanding microbial life and its impact on health and the environment.
method AI-driven approaches including machine learning and deep learning.
result Transformative role in enhancing microbial life understanding.
Detects and maps informal settlements in developing countries using satellite imagery.
problem Mapping informal settlements for aid delivery.
method Two methods: LR Sentinel-2 imagery and VHR satellite imagery.
result Successfully mapped informal settlements with LR satellite imagery.
This research creates efficient models for cyclo-stationary systems using generative methods.
problem Efficiently modeling systems with periodic forcing.
method Score-based generative modeling for reduced-order models.
result Accurately reproduces statistical properties and temporal correlations of cyclo-stationary time series.
MiniHack simplifies creation of complex RL environments.
problem Limited availability of challenging RL benchmarks.
method Develops a sandbox framework for easy RL environment design.
result MiniHack enables rapid creation of diverse RL testbeds.
Adaptive quadrature improves Bayesian inference through active learning.
problem Efficiently estimating posterior densities in Bayesian inference.
method Sequential node selection using acquisition functions, combining interpolative surrogate models and quadrature rules.
result Positive estimation of marginal likelihood with improved accuracy.
This paper proposes an original approach to cluster multi-component data sets, including an estimation of the number of clusters. From the construction of a minimal spanning tree with Prim's algorithm, and the assumption that the vertices are approximately distributed according to a Poisson distribution, the number of …
Paper proposes learning system dynamics from irregularly-sampled partial observations.
problem Capturing dynamics of multi-agent systems with irregular and partial observations.
method LG-ODE, a latent ordinary differential equation model using graph neural networks and neuralODE.
result Demonstrates effectiveness on motion capture, spring system, and charged particle datasets.
HighRes-net enhances satellite imagery by fusing multiple low-res views.
problem Super-resolving satellite imagery for reliable monitoring of human impact.
method End-to-end deep learning approach for multi-frame super-resolution.
result HighRes-net outperformed in European Space Agency's MFSR competition.
New machine learning model detects informal settlements in developing countries using low-res satellite data.
problem Lack of detailed maps for vulnerable populations in developing countries.
method Developed a new machine learning data set and demonstrated effective classification schemes for low-resolution satellite imagery.
result It is possible to detect informal settlements using low-resolution satellite data, making it more accessible for NGOs.
ELECTS model predicts crop type early from satellite data.
problem Early decision-making in crop type mapping.
method End-to-end deep learning model with modular design.
result ELECTS reduces data requirements for accurate early predictions.
Financial networks analyzed using statistical physics methods.
problem Understanding the dynamics of financial interactions and their impact.
method Statistical physics tools and complex network analysis.
result Introduced DebtRank to measure shock diffusion in financial systems.
The scientific data about the state of our planet, presented at the 2012 (Rio+20) summit, documented that today's human family lives even less sustainably than it did in 1992. The data indicate furthermore that the environmental impacts from our current economic activities are so large, that we are approaching situatio…
A compass guides institutions towards ecological economics goals.
problem Aligning institutional goals with ecological economics principles.
method Develops a policy compass for institutions, incorporating ecological economics principles.
result Adapted policy compass aligns institutional actions with ecological economics goals.
Macroeconomic theories of growth and wealth distribution have an outsized influence on national and international social and economic policies. Yet, due to a relative lack of reliable, system wide data, many such theories remain, at best, unvalidated and, at worst, misleading. In this paper, we introduce a novel econom…
GradientCoin aims to create a decentralized LLM system similar to Bitcoin.
problem Centralized LLMs are vulnerable to shutdown and data poisoning.
method Proposes a decentralized LLM system based on Bitcoin's architecture.
result The proposed system is unlikely to outperform standard Bitcoin.
New methods detect roads in low-res satellite data, overcoming visibility challenges.
problem Detecting roads in low-resolution satellite imagery, especially those hard to see.
method Two deep learning frameworks for ordinal classification of road types from satellite time series data.
result Models can identify large and medium-sized roads from Sentinel-2 imagery.
Cloud-native simulator studies global trading latencies.
problem Understanding latencies in planetary-scale automated trading systems.
method Cloud-native, open-source simulator with distributed clients.
result Demonstrates latencies in real-world trading systems.
Higher-order geometry modifies Newtonian dynamics and predicts anomalies in spacecraft motion.
problem Observing and understanding higher-order effects in general relativity.
method Generalizing the Einstein-Hilbert action to include higher-order infinitesimals and studying field equations and cosmologies.
result Higher-order corrections predict anomalies like the Pioneer and flyby effects.
Link quandles are shown to be residually finite.
problem Residual finiteness of link quandles.
method Proving residual finiteness of free products of residually finite quandles with residually finite associated groups.
result Link quandles are residually finite.
Finite vector bundles over complex manifolds are trivializable via finite covers.
problem Understanding when holomorphic vector bundles over compact complex manifolds are trivializable.
method Introducing finite bundles and using finite étale covers to trivialize holomorphic vector bundles.
result Holomorphic vector bundles over compact complex manifolds are finite if and only if they admit a flat holomorphic connection with finite monodromy.
Free and knot quandles are residually finite.
problem Residual finiteness of quandles.
method Definition and investigation of residual finiteness; proof for free and knot quandles; discussion on automorphism groups.
result Free and knot quandles are residually finite and Hopfian.
Abstract: Non-residually finite hyperbolic groups imply non-residually finite rigid hyperbolic groups.
problem Existence of non-residually finite hyperbolic groups
method Direct implication
result Existence of non-residually finite rigid hyperbolic groups
Finite type and finitely generated homotopy groups for manifold automorphisms.
problem Finite type and homotopy group properties of manifold automorphism spaces.
method Analyzing the classifying space of diffeomorphism groups and using simple homotopy theory.
result The classifying space of diffeomorphism groups has finitely generated homotopy groups.