Hasil untuk "Dramatic representation. The theater"

Sergio Lo Gatto

A conversation with the British actor and director Sam Crane, co-author alongside Pinny Grylls of the documentary Grand Theft Hamlet (UK, 2024, 91’).

Dorota Semenowicz

Una Chaudhuri, autorka pionierskiego dla teatru ekologicznego artykułu „«There Must Be a Lot of Fish in That Lake»: Toward an Ecological Theater” z 1994, nawołuje dziś wyraźnie do tworzenia teatru międzygatunkowego. Jego podstawowymzałożeniem jest uznanie materialności gatunków nie-ludzkich i odejście od wykorzystywania natury jako metafory. Co owa materialność oznacza jednak w praktyce i jak myśleć o niej w kontekście obecności zwierząt na scenie? Niniejszy artykuł jest próbą zawieszenia etycznego esencjonalizmu, z góry wkluczającego udział żywych zwierząt w teatrze, a często kryjącego tylko pragnienie moralnego oczyszczenia, oraz zaproponowania racjonalnych ram dyskusji na temat obecności gatunków nie-ludzkich na scenie. Autorka skupia się na spektaklu Hate: Un duo avec un cheval w reżyserii Laetitii Dosch (2018), w którym z aktorką wystąpił koń. Przygląda się mu z perspektywy zooësis, czyli zaproponowanego przez Chaudhuri terminu obejmującego sposoby, w jakie „zwierzę jest w dyskursie konstruowane, reprezentowane, pojmowane i źle pojmowane”. Interesują ją trzy kwestie: 1) proces budowania podmiotowości konia i koncepcja natury w spektaklu; 2) relacja aktorka–zwierzę w kontekście ekologii feministycznej; 3) proces produkcji spektaklu. Zderza ponadto przedstawienie z innymi przykładami twórczości, w której zwierzęta pojawiają się na scenie nie jako symbol, lecz realna obecność.

Théo Hanon, Nicolas Mil-Homens Cavaco, John Kiely et al.

Representing and processing data in spherical domains presents unique challenges, primarily due to the curvature of the domain, which complicates the application of classical Euclidean techniques. Implicit neural representations (INRs) have emerged as a promising alternative for high-fidelity data representation; however, to effectively handle spherical domains, these methods must be adapted to the inherent geometry of the sphere to maintain both accuracy and stability. In this context, we propose Herglotz-NET (HNET), a novel INR architecture that employs a harmonic positional encoding based on complex Herglotz mappings. This encoding yields a well-posed representation on the sphere with interpretable and robust spectral properties. Moreover, we present a unified expressivity analysis showing that any spherical-based INR satisfying a mild condition exhibits a predictable spectral expansion that scales with network depth. Our results establish HNET as a scalable and flexible framework for accurate modeling of spherical data.

Ana Durica, John Booth, Ivana Drobnjak

Paediatric kidney disease varies widely in its presentation and progression, which calls for continuous monitoring of renal function. Using electronic health records collected between 2019 and 2025 at Great Ormond Street Hospital, a leading UK paediatric hospital, we explored a temporal modelling approach that integrates longitudinal laboratory sequences with demographic information. A recurrent neural model trained on these data was used to predict whether a child would record an abnormal serum creatinine value within the following thirty days. Framed as a pilot study, this work provides an initial demonstration that simple temporal representations can capture useful patterns in routine paediatric data and lays the groundwork for future multimodal extensions using additional clinical signals and more detailed renal outcomes.

ANA MARIA NOGUERA DURAN

Antígonas Tribunal de Mujeres: archivos y repertorios poéticos de la memoria de una nación en guerra y transformación – Este articulo analiza a partir de una perspectiva de la investigación en performance política, el proceso de creación de la obra teatro Antígonas Tribunal de Mujeres, integrada por víctimas y sobrevivientes del conflicto interno y la guerra en Colombia, quienes comparten en común haber padecido crímenes de Estado. Tomando como objeto de estu-dio este caso, indaga las rutas metodológicas de creación que, estas mujeres han creado para trans-formar sus propias historias de dolor y resistencia, en archivos y repertorios poéticos. Los cuales pos-tulamos como formas de producción y transmisión de conocimiento incorporado, sobre la memoria de una nación marcada por la violencia.

Goutham Rajendran, Simon Buchholz, Bryon Aragam et al.

To build intelligent machine learning systems, there are two broad approaches. One approach is to build inherently interpretable models, as endeavored by the growing field of causal representation learning. The other approach is to build highly-performant foundation models and then invest efforts into understanding how they work. In this work, we relate these two approaches and study how to learn human-interpretable concepts from data. Weaving together ideas from both fields, we formally define a notion of concepts and show that they can be provably recovered from diverse data. Experiments on synthetic data and large language models show the utility of our unified approach.

Janosch Jungo, Yutong Xiang, Shkurta Gashi et al.

Wearable devices continuously collect sensor data and use it to infer an individual's behavior, such as sleep, physical activity, and emotions. Despite the significant interest and advancements in this field, modeling multimodal sensor data in real-world environments is still challenging due to low data quality and limited data annotations. In this work, we investigate representation learning for imputing missing wearable data and compare it with state-of-the-art statistical approaches. We investigate the performance of the transformer model on 10 physiological and behavioral signals with different masking ratios. Our results show that transformers outperform baselines for missing data imputation of signals that change more frequently, but not for monotonic signals. We further investigate the impact of imputation strategies and masking rations on downstream classification tasks. Our study provides insights for the design and development of masking-based self-supervised learning tasks and advocates the adoption of hybrid-based imputation strategies to address the challenge of missing data in wearable devices.

Giovanni Boccia Artieri

Negli anni della pandemia, si è assistito a un’ampia sperimentazione nel campo dello spettacolo dal vivo, che ha visto la nascita di nuove forme artistiche sfruttando le potenzialità, ma anche i limiti, delle piattaforme digitali. Questo saggio si propone di delineare la natura degli Oggetti Teatrali Online Non Identificati (OTONI) come una realtà distintiva, analizzandoli attraverso il concetto di mediatizzazione. La mediatizzazione degli OTONI coinvolge sia la loro forma drammaturgica sia quella performativa, caratterizzandosi per un nuovo tipo di patto empatico con lo spettatore, per la loro natura deterritorializzata ed effimera now everywhere, e per l'assimilazione di logiche e linguaggi digitali sia nella strutturazione formale che nella drammaturgia.

Katarzyna Lisiecka, Adam Regiewicz

Wprowadzenie do bloku tematycznego poświęconego relacji między operą a kulturą popularną.

Enrico Vicenti

Tjeerd V. olde Scheper

The representation of arbitrary data in a biological system is one of the most elusive elements of biological information processing. The often logarithmic nature of information in amplitude and frequency presented to biosystems prevents simple encapsulation of the information contained in the input. Criticality Analysis (CA) is a bio-inspired method of information representation within a controlled self-organised critical system that allows scale-free representation. This is based on the concept of a reservoir of dynamic behaviour in which self-similar data will create dynamic nonlinear representations. This unique projection of data preserves the similarity of data within a multidimensional neighbourhood. The input can be reduced dimensionally to a projection output that retains the features of the overall data, yet has much simpler dynamic response. The method depends only on the rate control of chaos applied to the underlying controlled models, that allows the encoding of arbitrary data, and promises optimal encoding of data given biological relevant networks of oscillators. The CA method allows for a biologically relevant encoding mechanism of arbitrary input to biosystems, creating a suitable model for information processing in varying complexity of organisms and scale-free data representation for machine learning.

Rogier van der Sluijs, Nandita Bhaskhar, Daniel Rubin et al.

Image augmentations are quintessential for effective visual representation learning across self-supervised learning techniques. While augmentation strategies for natural imaging have been studied extensively, medical images are vastly different from their natural counterparts. Thus, it is unknown whether common augmentation strategies employed in Siamese representation learning generalize to medical images and to what extent. To address this challenge, in this study, we systematically assess the effect of various augmentations on the quality and robustness of the learned representations. We train and evaluate Siamese Networks for abnormality detection on chest X-Rays across three large datasets (MIMIC-CXR, CheXpert and VinDR-CXR). We investigate the efficacy of the learned representations through experiments involving linear probing, fine-tuning, zero-shot transfer, and data efficiency. Finally, we identify a set of augmentations that yield robust representations that generalize well to both out-of-distribution data and diseases, while outperforming supervised baselines using just zero-shot transfer and linear probes by up to 20%. Our code is available at https://github.com/StanfordMIMI/siaug.

Flávio Desgranges

O autor aborda, no presente texto, processos de criação artística realizados com espectadores tendo como base uma proposição teatral. Logo após o espetáculo, o público é convidado a se debruçar sobre a cena assistida para, a partir da concepção desenvolvida pelos artistas no processo de criação, elaborar uma leitura poética, efetivada como uma outra cena, surgida das entranhas dos processos de recepção, tendo em vista o impacto ocasionado pela obra nos espectadores.

André Gardel

ABSTRACT – Anthropophagic-Perspectivistic Poetics for a Re-Vision of the Brazilian Theater: the scene of origin – This text presents a plan of construction of a Poetics, whose purpose is to effect a Re-Vision, in five key moments, of the Brazilian Theater. To do this, we seek to establish a scene of origin, outlined after the meeting – impregnated with attraction and repulsion – that takes place in Brazil, from the sixteenth century, between Amerindian and European civilizations. Two metaphysics and forms of expression thus form the intensive and pantheatrical basis of a Poetics that projects a notion of Brazilian theater in a constant state of struggles of perspectives, symbolized, in its origins, by two anthropophagic mouths interdevouring: the mercantilist Christian Eucharist and the Amerindian cosmopolitical.

Walter Lima Torres Neto

Neste ensaio, procuramos introduzir uma tentativa de resposta à pergunta: Por que o teatro viaja, e para que o teatro viaja? Nossa hipótese é que o teatro viaja desde sempre. E o motivo da viagem está associado a uma busca de reconhecimento e gratificação. Sugerimos algumas pistas oriundas da mitologia do próprio teatro para tentar explicitar a condição deste nomadismo teatral que nos chega até os dias de hoje em condições diferentes.

Yaning Li, Xue Wang, Hao Zhu et al.

Existing light field representations, such as epipolar plane image (EPI) and sub-aperture images, do not consider the structural characteristics across the views, so they usually require additional disparity and spatial structure cues for follow-up tasks. Besides, they have difficulties dealing with occlusions or larger disparity scenes. To this end, this paper proposes a novel Epipolar Focus Spectrum (EFS) representation by rearranging the EPI spectrum. Different from the classical EPI representation where an EPI line corresponds to a specific depth, there is a one-to-one mapping from the EFS line to the view. Accordingly, compared to a sparsely-sampled light field, a densely-sampled one with the same field of view (FoV) leads to a more compact distribution of such linear structures in the double-cone-shaped region with the identical opening angle in its corresponding EFS. Hence the EFS representation is invariant to the scene depth. To demonstrate its effectiveness, we develop a trainable EFS-based pipeline for light field reconstruction, where a dense light field can be reconstructed by compensating the "missing EFS lines" given a sparse light field, yielding promising results with cross-view consistency, especially in the presence of severe occlusion and large disparity. Experimental results on both synthetic and real-world datasets demonstrate the validity and superiority of the proposed method over SOTA methods.

Masoud Kamgarpour, GyeongHyeon Nam, Anna Puskás

We study character varieties arising as moduli of representations of an orientable surface group into a reductive group $G$. We first show that if $G/Z$ acts freely on the representation variety, then both the representation variety and the character variety are smooth and equidimensional. Next, we count points on a family of smooth character varieties; namely, those involving both regular semisimple and regular unipotent monodromy. In particular, we show that these varieties are polynomial count and obtain an explicit expression for their $E$-polynomials. Finally, by analysing the $E$-polynomial, we determine certain topological invariants of these varieties such as the Euler characteristic and the number of connected components. As an application, we give an example of a cohomologically rigid representation which is not physically rigid.

Gabriela Pérez Cubas, José Luis Valenzuela

Cuerpo del Drama es un dossier publicado por el Gitce (Grupo de investigación en técnicas de la corporeidad para la escena) perteneciente al Centro de Investigaciones Dramáticas, Facultad de Arte, Universidad Nacional del Centro de la Provincia de Buenos Aires. Este dossier se propone divulgar distintas producciones (puestas en escena, ensayística, dramaturgia, etc.) cuyos enfo- ques aborden el análisis de la corporeidad en la escena teatral. Si bien por sus características la corporeidad teatral nos centra en el estudio de la práxis escénica creemos que su estudio articulado con otras perspectivas del conocimiento, tales como la filosofía, la antropología o la sociología, entre otras, puede enriquecer los debates sobre un objeto de estudio tan vasto y a la vez inaprehensible. Es también de nuestro interés articular los ámbitos académicos e independien- tes de la producción y la reflexión teatral, con el objeto de nutrir ambos enfo- ques por medio del intercambio productivo de ideas y experiencias. Por tales motivos, invitamos a quienes les interese difundir sus trabajos a comunicarse con el siguiente correo electrónico: cuerpodeldrama@gmail.com. Esperando disfruten esta primera entrega

Aparna R Nambiar

This article analyzes two recent works of contemporary Southeast Asian dance staged in Singapore: Indonesian dancer Rianto’s Medium (2018) and Behalf (2018) by Thai Dancer Pichet Klunchun and Taiwanese Dancer Chen-Wu Kang. I identify an emerging epoch of intense, cross-generic experimentation, as traditional cultural practices negotiate with lapsed identifications with the postcolonial nation as well as the overwhelming demands of the neoliberal art market. Highlighting the conditions of dance-making in the region, I offer “generic engineering” as a conceptual container for experiments that interweave traditional Asian dance forms with Western contemporary art practices to consolidate new, transnational spectatorial communities.

Chaitanya K. Joshi, Fayao Liu, Xu Xun et al.

Knowledge distillation is a learning paradigm for boosting resource-efficient graph neural networks (GNNs) using more expressive yet cumbersome teacher models. Past work on distillation for GNNs proposed the Local Structure Preserving loss (LSP), which matches local structural relationships defined over edges across the student and teacher's node embeddings. This paper studies whether preserving the global topology of how the teacher embeds graph data can be a more effective distillation objective for GNNs, as real-world graphs often contain latent interactions and noisy edges. We propose Graph Contrastive Representation Distillation (G-CRD), which uses contrastive learning to implicitly preserve global topology by aligning the student node embeddings to those of the teacher in a shared representation space. Additionally, we introduce an expanded set of benchmarks on large-scale real-world datasets where the performance gap between teacher and student GNNs is non-negligible. Experiments across 4 datasets and 14 heterogeneous GNN architectures show that G-CRD consistently boosts the performance and robustness of lightweight GNNs, outperforming LSP (and a global structure preserving variant of LSP) as well as baselines from 2D computer vision. An analysis of the representational similarity among teacher and student embedding spaces reveals that G-CRD balances preserving local and global relationships, while structure preserving approaches are best at preserving one or the other. Our code is available at https://github.com/chaitjo/efficient-gnns